{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "01_Keras_stateful_RNN_solution.ipynb",
      "version": "0.3.2",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true,
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/GoogleCloudPlatform/tensorflow-without-a-phd/blob/master/tensorflow-rnn-tutorial/01_Keras_stateful_RNN_solution.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "metadata": {
        "id": "RH-br21Mfg83",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# An stateful RNN model to generate sequences\n",
        "RNN models can generate long sequences based on past data. This can be used to predict stock markets, temperatures, traffic or sales data based on past patterns. They can also be adapted to [generate text](https://docs.google.com/presentation/d/18MiZndRCOxB7g-TcCl2EZOElS5udVaCuxnGznLnmOlE/pub?slide=id.g139650d17f_0_1185). The quality of the prediction will depend on training data, network architecture, hyperparameters, the distance in time at which you are predicting and so on. But most importantly, it will depend on wether your training data contains examples of the behaviour patterns you are trying to predict.\n",
        "\n",
        "This is the solution notebook. The corresponding work notebook is [01_Keras_stateful_RNN_playground.ipynb](https://colab.research.google.com/github/GoogleCloudPlatform/tensorflow-without-a-phd/blob/master/tensorflow-rnn-tutorial/01_Keras_stateful_RNN_playground.ipynb)\n"
      ]
    },
    {
      "metadata": {
        "id": "9l96vOsPfg84",
        "colab_type": "code",
        "outputId": "26f4ea7b-0ee1-4ea1-f332-ac96e29814a7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "cell_type": "code",
      "source": [
        "import math\n",
        "import numpy as np\n",
        "from matplotlib import pyplot as plt\n",
        "import tensorflow as tf\n",
        "tf.enable_eager_execution()\n",
        "print(\"Tensorflow version: \" + tf.__version__)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Tensorflow version: 1.13.1\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "gxJ60M-4ilJy",
        "colab_type": "code",
        "cellView": "form",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#@title Data formatting and display utilites [RUN ME]\n",
        "\n",
        "def dumb_minibatch_sequencer(data, batch_size, sequence_size, nb_epochs):\n",
        "    \"\"\"\n",
        "    Divides the data into batches of sequences in the simplest way: sequentially.\n",
        "    :param data: the training sequence\n",
        "    :param batch_size: the size of a training minibatch\n",
        "    :param sequence_size: the unroll size of the RNN\n",
        "    :param nb_epochs: number of epochs to train on\n",
        "    :return:\n",
        "        x: one batch of training sequences\n",
        "        y: one batch of target sequences, i.e. training sequences shifted by 1\n",
        "    \"\"\"\n",
        "    data_len = data.shape[0]\n",
        "    nb_batches = data_len // (batch_size * sequence_size)\n",
        "    rounded_size = nb_batches * batch_size * sequence_size\n",
        "    xdata = data[:rounded_size]\n",
        "    ydata = np.roll(data, -1)[:rounded_size]\n",
        "    xdata = np.reshape(xdata, [nb_batches, batch_size, sequence_size])\n",
        "    ydata = np.reshape(ydata, [nb_batches, batch_size, sequence_size])\n",
        "\n",
        "    for epoch in range(nb_epochs):\n",
        "        for batch in range(nb_batches):\n",
        "            yield xdata[batch,:,:], ydata[batch,:,:]\n",
        "            \n",
        "            \n",
        "def rnn_minibatch_sequencer(data, batch_size, sequence_size, nb_epochs):\n",
        "    \"\"\"\n",
        "    Divides the data into batches of sequences so that all the sequences in one batch\n",
        "    continue in the next batch. This is a generator that will keep returning batches\n",
        "    until the input data has been seen nb_epochs times. Sequences are continued even\n",
        "    between epochs, apart from one, the one corresponding to the end of data.\n",
        "    The remainder at the end of data that does not fit in an full batch is ignored.\n",
        "    :param data: the training sequence\n",
        "    :param batch_size: the size of a training minibatch\n",
        "    :param sequence_size: the unroll size of the RNN\n",
        "    :param nb_epochs: number of epochs to train on\n",
        "    :return:\n",
        "        x: one batch of training sequences\n",
        "        y: one batch of target sequences, i.e. training sequences shifted by 1\n",
        "    \"\"\"\n",
        "    data_len = data.shape[0]\n",
        "    # using (data_len-1) because we must provide for the sequence shifted by 1 too\n",
        "    nb_batches = (data_len - 1) // (batch_size * sequence_size)\n",
        "    assert nb_batches > 0, \"Not enough data, even for a single batch. Try using a smaller batch_size.\"\n",
        "    rounded_data_len = nb_batches * batch_size * sequence_size\n",
        "    xdata = np.reshape(data[0:rounded_data_len], [batch_size, nb_batches * sequence_size])\n",
        "    ydata = np.reshape(data[1:rounded_data_len + 1], [batch_size, nb_batches * sequence_size])\n",
        "\n",
        "    whole_epochs = math.floor(nb_epochs)\n",
        "    frac_epoch = nb_epochs - whole_epochs\n",
        "    last_nb_batch = math.floor(frac_epoch * nb_batches)\n",
        "    \n",
        "    for epoch in range(whole_epochs+1):\n",
        "        for batch in range(nb_batches if epoch < whole_epochs else last_nb_batch):\n",
        "            x = xdata[:, batch * sequence_size:(batch + 1) * sequence_size]\n",
        "            y = ydata[:, batch * sequence_size:(batch + 1) * sequence_size]\n",
        "            x = np.roll(x, -epoch, axis=0)  # to continue the sequence from epoch to epoch (do not reset rnn state!)\n",
        "            y = np.roll(y, -epoch, axis=0)\n",
        "            yield x, y\n",
        "            \n",
        "\n",
        "plt.rcParams['figure.figsize']=(16.8,6.0)\n",
        "plt.rcParams['axes.grid']=True\n",
        "plt.rcParams['axes.linewidth']=0\n",
        "plt.rcParams['grid.color']='#DDDDDD'\n",
        "plt.rcParams['axes.facecolor']='white'\n",
        "plt.rcParams['xtick.major.size']=0\n",
        "plt.rcParams['ytick.major.size']=0\n",
        "plt.rcParams['axes.titlesize']=15.0\n",
        "\n",
        "\n",
        "def display_lr(lr_schedule, nb_epochs):\n",
        "  x = np.arange(nb_epochs)\n",
        "  y = [lr_schedule(i) for i in x]\n",
        "  plt.figure(figsize=(9,5))\n",
        "  plt.plot(x,y)\n",
        "  plt.title(\"Learning rate schedule\\nmax={:.2e}, min={:.2e}\".format(np.max(y), np.min(y)),\n",
        "            y=0.85)\n",
        "  plt.show()\n",
        "  \n",
        "def display_loss(history, full_history, nb_epochs):\n",
        "  plt.figure()\n",
        "  plt.plot(np.arange(0, len(full_history['loss']))/steps_per_epoch, full_history['loss'], label='detailed loss')\n",
        "  plt.plot(np.arange(1, nb_epochs+1), history['loss'], color='red', linewidth=3, label='average loss per epoch')\n",
        "  plt.ylim(0,3*max(history['loss'][1:]))\n",
        "  plt.xlabel('EPOCH')\n",
        "  plt.ylabel('LOSS')\n",
        "  plt.xlim(0, nb_epochs+0.5)\n",
        "  plt.legend()\n",
        "  for epoch in range(nb_epochs//2+1):\n",
        "    plt.gca().axvspan(2*epoch, 2*epoch+1, alpha=0.05, color='grey')\n",
        "  plt.show()\n",
        "\n",
        "def picture_this_7(features):\n",
        "    subplot = 231\n",
        "    for i in range(6):\n",
        "        plt.subplot(subplot)\n",
        "        plt.plot(features[i])\n",
        "        subplot += 1\n",
        "    plt.show()\n",
        "    \n",
        "def picture_this_8(data, prime_data, results, offset, primelen, runlen, rmselen):\n",
        "    disp_data = data[offset:offset+primelen+runlen]\n",
        "    colors = plt.rcParams['axes.prop_cycle'].by_key()['color']\n",
        "    plt.subplot(211)\n",
        "    plt.xlim(0, disp_data.shape[0])\n",
        "    plt.text(primelen,2.5,\"DATA |\", color=colors[1], horizontalalignment=\"right\")\n",
        "    plt.text(primelen,2.5,\"| PREDICTED\", color=colors[0], horizontalalignment=\"left\")\n",
        "    displayresults = np.ma.array(np.concatenate((np.zeros([primelen]), results)))\n",
        "    displayresults = np.ma.masked_where(displayresults == 0, displayresults)\n",
        "    plt.plot(displayresults)\n",
        "    displaydata = np.ma.array(np.concatenate((prime_data, np.zeros([runlen]))))\n",
        "    displaydata = np.ma.masked_where(displaydata == 0, displaydata)\n",
        "    plt.plot(displaydata)\n",
        "    plt.subplot(212)\n",
        "    plt.xlim(0, disp_data.shape[0])\n",
        "    plt.text(primelen,2.5,\"DATA |\", color=colors[1], horizontalalignment=\"right\")\n",
        "    plt.text(primelen,2.5,\"| +PREDICTED\", color=colors[0], horizontalalignment=\"left\")\n",
        "    plt.plot(displayresults)\n",
        "    plt.plot(disp_data)\n",
        "    plt.axvspan(primelen, primelen+rmselen, color='grey', alpha=0.1, ymin=0.05, ymax=0.95)\n",
        "    plt.show()\n",
        "\n",
        "    rmse = math.sqrt(np.mean((data[offset+primelen:offset+primelen+rmselen] - results[:rmselen])**2))\n",
        "    print(\"RMSE on {} predictions (shaded area): {}\".format(rmselen, rmse))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "ouNkUJLBfg89",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "## Generate fake dataset"
      ]
    },
    {
      "metadata": {
        "id": "QLTqiqjSfg8-",
        "colab_type": "code",
        "outputId": "97eeff5f-ef4e-4747-bb58-9b425635bd09",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 375
        }
      },
      "cell_type": "code",
      "source": [
        "WAVEFORM_SELECT = 0# select 0, 1 or 2\n",
        "\n",
        "def create_time_series(datalen):\n",
        "    # good waveforms\n",
        "    frequencies = [(0.2, 0.15), (0.35, 0.3), (0.6, 0.55)]\n",
        "    freq1, freq2 = frequencies[WAVEFORM_SELECT]\n",
        "    noise = [np.random.random()*0.1 for i in range(datalen)]\n",
        "    x1 = np.sin(np.arange(0,datalen) * freq1)  + noise\n",
        "    x2 = np.sin(np.arange(0,datalen) * freq2)  + noise\n",
        "    x = x1 + x2\n",
        "    return x.astype(np.float32)\n",
        "\n",
        "DATA_LEN = 1024*128+1\n",
        "data = create_time_series(DATA_LEN)\n",
        "plt.plot(data[:512])\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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2myWtd4Qc0BpRQoFjxEFcWlCF9H7nEACcOTqIbLFmuz5pNnIoHu1SSMdJSBOd\nsZlUz4mxeHshHQl6MBYPYHYla7vNKADIFcWuE7sZg+Fmcjf1SRNtWE8evBnFYELbbtdm9jMetFFg\nZ3Rbuy9evIg/+IM/wNraGlwuF5555hk8/PDDmJycxKOPPooHH3wQ58+fh9frxR133LGvrbtfKFUl\nXZU0AAh4XRDrMuoNec/ZwATBKtKDYW/bkT2McDMcxW6jbFhIUrdhY0BrREm+VMPw4P6/H+LWRVEU\nXF5MYTQWOPA8uu14DM+/uY4ri+l9BQNvpJozsrsW0s0HunWbPawRh89GqoSgz6XNH2/HyckBPP/m\nOrbSZVudQ4qiIF+s7ev82o9Y89xL56uYHOnfahyhn/VkCYNhb0etoBPDrcCxvUZk8cp2uoxwwK1N\nJ+pHdAvpc+fO4Rvf+Ebbz3/qU5/Cpz71Kb1vbzsURUGxLGFE5wN8oDlLulKr921EPGGMnUL6IMI2\ntXYz4R/uMiUVaCWr5my2eUAcLoWyhEJZwu3H969GA8CZY4MAgKtLGfzSPfbJ8WhVpLu7HwV8bgyE\nvbarehCHiywr2EqVMDUWPtCBd2pqEM+/uY651aythHRVbECsy4jquBcBrRFYaRqBReyBVG8gmSnj\n9umD70MAMDHc3OS0UXK3oijYzlQwNdq/1WjAwh7pWw1WTdZdkW5+HY3AItqRYX2P+8yPZtjV2q13\nbiewY5Y0CWliHzabvZ1jQ4EDX3viSBQupwNXltJWL8tUUrkKHEJnm267GY8HsZUpo96gEVjE3mQK\nVYh1WWsF2I9TU2qf9OyyvfqkjdyLgFY+QYas3cQebKbU8XETHdi6gZY12k4jsHJFEaLUwMjgwfda\nO0NC2iSKTcES0llNDmizpO1VQSQOj2yxBpdT6Mj2bFchnW0+vAzoEtLNHmmaJU3sAxPSnYgAt8uJ\nk5NRXF/PoyraZ5MzlatiIOyDU0eb0PhQELKsYDtjr75w4vDY6KK388RkFIIAzK3aS0jrnSHNiO+w\ndhPEbro5hwBgNBaAwyFgPWEftxC7h5CQJjqi1OztDOro7QTUsDGAKtJEezKFGgZC3o7C7Jg1umgz\na7ehinSIKtLEwbC04U5tpmeOxdCQFdskDyuKgnS+2nV/NINZCMneTbRjs4tzKOBzY2IohLlVewWO\nZQ1WpAeabpAMWbuJPVhPqpXliaHObM8upwNjsYCtKtIspHMk1t+ZNSSkTcJISBLQsnbTqARiLxRF\nQTZfxUAHtm4A8Lqd8LgcyNusIp0rinA4Oqu670azdlNqN7EPWymWNtzZLjnrk7ZLRS1fEiHVZf1C\nOq4+2Nmp8kEcLptdnkPHxsP7mNHHAAAgAElEQVQoV+u2qs7mmZDWWZFm97ASuQyJPWDXV7Zx2QkT\nwyHkS6KmN3gn0axIj1JFmuiEosGKdMBH1m6iPeVqHWJd7qrnMRz0aC0HdiFXrCES9MDh6H6EHPVI\nE52wkSpBEFSrXCcMNQO7cjbZoGFipdugMcZws3qQzFZMWxPRXySax8ZBqfcMllq9um2faho73/VW\npP1eFxxCy61IEDthFelOWowYbBpJyibX5lZFmoQ00QEloxVpL1m7ifZkmjOku+kdDgc8tht/lSvW\ndPVHA62+cBLSxH5spsqIR/1wu5wdvT7oV6/NdnkgZgJYb0WanUd2qXoQhw87xoY63KyZHFFdDrYS\n0qxHWuccaUEQEPC5qSJN7MlGsoRYxAdfB6OvGOyanszZQ0hvZ9R1DlNFmugE1osaOmCmYjv8JKSJ\nfdBGX3Vo7QbUY7FUraNhk/Rdqd5AqVrX5kF3i8vpQMjvRo7Cxog2SPUGUrlKV1WAoM0smq3RV/qE\nNNsMLlZoQ4rYm2S2gmjIA4+7s82olpAuWLksU9HyOoL6NnYBIOB3o0wbUsQupLqMRLbScdAYIx5p\nVqRz9miR2EqXEfS7dRcY7QIJaZNgD1mGx1/V6KJL3Ey2ixnSDLtVloxa6QDV3k0VaaIdm6kyFKXz\n3k6gdU23S0VaE9IRfdZuTUjbLKiQOBwURUEyV+3Y1g20RvfYqSLN7iN6N3YBIOhzoUTFEWIX6XwV\nigIMd3EOAcDQgLo5agdrt6IoSGTKGBns76AxgIS0abBZgbr7aZo90hQ2RuwFs3az2ZSdYLcRWEbn\ndgItIW2ndFji8GA9W50mdgOA1+OE0yHYSEg3rd0D+irSTqcDfq+LhDSxJ4WyBFFqdGzrBtRCwVDU\nZyshnc5X4XE5NLegHoJ+Nyq1Ohoy3Y+IFto1ukvXEMu9SNkgtC9fElEV+3+GNEBC2jSSWfXA7maX\ndicsbKxCu5fEHrCK9EBXFWl7VZZaFWn9FYBoyAtZVqgKQOwJG+nUTUXabr2OKYNhY4DaFkLWbmIv\nWH90t9W0yZEwktmKLYoFiqJgI1nCaDzY0bjJdjA3S8Um1w7icGCuoVjXQtp3w9fzDJsh3Wmop50h\nIW0SyVwFHrdTEy/dEvA2rd0kAIg9YLMo9Vi77TICi83t1Bs2BuwcgUV90sTNdDP/dichvxulij2u\nzelcFQGfy1AlLez3oGCTDTjicEl2mdjNYH3SazaoSueKIiq1Oia67GHdDSuQ0MYusZNWjkV351DA\n54bf67LFRAWjxUU7QULaJJLZCoYHfLp3L2n8FbEfWmp3F0KazSe8upSxZE1mY5a1G6DkbmJvFjfy\nEITWQ32nBP0u+1SkcxXEuggl3ItQQLWk1m0SVEgcHt2OvmLYKXCMjSaaGO7uOrEbVpGm5zpiJ3qt\n3YDaJ22HijQ75vs9aAwgIW0KNamBfEk0tPPidjngcgoo28D2RBw+6XwVPo+zqyrT3adH4HE78cKb\na7boGTYjJZWENNEOWVYwt5rFkeGQFu7YKQGfGzWxwb2wlOoNFMqSKUIasE/AGnF46K9I22eW9HpC\nda4YrUgHtQR8Oo+IFummEO4mZ4ARj/hRKIuoSQ2zl2UqzF3L8p/6GRLSJpDSeWPZiSAI8HvdZO0m\n9iSZVVNSu3E8+Lwu3Hv7CNYSJSxv8l8F0Hqkw/p7pCNNEZ4jazexi/VkEeVqHSenBrr+Wm0EFucP\nxKwFxLCQ9tsr8Z84PPQKaTbqZzNVNn1NZtOqSBu1djcr0nQeETtI5atwCN216jFYX3Wa86o0y0Jg\nbav9DAlpE9BrddpNwOciCxBxE1WxjkJZ1LV7+cBdEwCAF95aN3tZpmNKj3SIKtLE3syuZAEAp3QI\n6ZBNZkmnWbq/QSHNsj7skvhPHB6JbAWC0L0tlR2TrE2JZ9aTrCJt0Nrtpx5p4mZSuQoGwl44nd1L\nMKYzkjm++6SZlglQRZroBL0plrsZHvQjna+SmCZuQLMB6Ti+7r19FB6XwxZCOleswW1w3AhZu4l2\nzDWF9Ompwa6/NmCTWdJ6Qgn3IkizpIk2JLMVDIa9cHUpAtwuB8IBD9I2GN2zkSjB43YadnYEqEea\n2IWiKEjlqojpnKpgl+Ru1qZq5HnOLpCQNgG9VqfdnJoahKIA82s5M5ZF9AlJA3NhAz43bjsew/Jm\nASLnPTW5Yg3RoMfQuBES0kQ7ZleycDgETB+Jdv21trF2m1SRDgXI2k3cjCwrSOUqup91BiNeZAp8\nt90oioKNVBETQ0E4HPrvRYB9rhvE4ZEviZDqMuI6r9HMmZjmvCLNrN3UI010hFnW7lOTquVwdjlr\neE1E/6Bt1OjcwWTikvebea4kImqwksaCynIlvh/WiMOl0ZAxv5bDsbEwvG5n119vF4smq/bFIsbO\no9YMetqQIlrkijXUG4ruZ51Y2IdSReI6KClbqKFSa2g93UYI0vgrYhfsGq0nsRto9UgnOa9IV5rH\nfLfBnnaEhLQJGBU6jFNHm0J6xR7jiojDweg8Pjskh1ZqddTEhqHRV4Daj+N0CFSRJm5geUt1ZJzS\nYesGWmNseN+Malm7jYaN8X/NIA6fhNbGFtD19YPNDZ4Mx/buVn+0cSFN1m5iN3pnSDNa1m6bVKQ9\n3W9c2w0S0iaQzFbg97o0waKX0VgA4YBHC8UhCKBl7dYrpEM26Hc0azNKEAREgh4S0sQNrG6pKbzH\nxyO6vt4uFs1WRdocazeFjRE72Wombo/G9AlpdlyyDR8eWU+o14pxg0FjwI6QQs6vG8ThYWSGNKC6\n7hwC3+cQoG4eeT1OXYFqdqP/f8JDIJnV3zO0E0EQcGpqAFvpMgkBQqMlMvVdeFv9jvweU2a1RwBA\nNOSl84e4Aa2SNmjM1cF7ane2UIXH7TSclGqHzTfi8NnKGBPSA2H+k7tZ8r3R8FgACJCQJnbRqkjr\ne55zOAQE/W7u3ULlah2BWyBoDCAhbZhyVUKpWjflogu0RrPMUVWaaJLKVuHzOHU7Huxg00xkzEm+\nB9Se8FJFglSXDb8X0R8ksqoA0Ht82cXanc7XMBj2GgrsA3ZsvpGQJnawlVbPoxHdFWn+rd3smA8F\njPd2elwOuJwCytQjTTQxau0GgJDfgxLHhRFAtXbfCondAAlpw6QMjCbaCyakqU+aYCRzFcSjft0P\nx6EA/9WlpMGK4U5YtWQ9WTT8XkR/0Dq+9AkAO1i7G7KCbLFm2NYNAAGvCw6BbxcLcfhsMyGt8zrN\n0uTTHCd3s3M8ZLBVD1BdhgGfm3snC3F4mDFZIRhwc/08B6jjr26FGdIACWnDMAtpNOQx5f2OjKh9\nOcyKSNza1KQG8iURQzpGXzFsUZFmFUMThDTrg11czxt+L6I/SGQr8LidWhp1t7SENL+VpXypBllW\ntEAnIzD7YIHzhzXicNlKlxAOeHQn8bL55lxXpJv3SaOZN4yg301hY4RGqSLBIcCQ7Tnkd0Osy9yO\nNG00ZNTExi2R2A2QkDYM22kMmnTA2MVCSBwOKYNBY4BqAwL4PqaYtdto2BgATE+oc4IXN0hIEyrJ\nbAXDA/pdHQGvC4LAd490tlnlixlM7GaEAvzbB4nDQ5YVbGcqGI3rc3UAO8LGOK5Ia9Zus4S0z4Ui\nxxtwnSDLChRF6fUy+oJSRYLf5zY0o5z34khFVAU+WbuJjiiZvHvJwimop4YA1P5owJjA1KzdHD8U\nJ7MVDIS88OiY8bubY82K9PX1nOH3Omxev7KNpU3aADCTmtRAriga6r93OAT4vS6uN6NYYrcRy+BO\nQn7+7YPE4ZEpVCHVZYzqbI8A1Adrr8epHas8UqyI8HtdpqUNB3xuiFID9YY9MztEqYFPf/EH+LPv\nvN3rpfQFpYpkWC+0Miz4fKZjDgw/WbuJTjBbSLNwCp4rH8ThYUaadZDzBF5FUZDIVjBkgq0bUMPG\n4lGf7SrSotTAF/7iJfzhN1/r9VL6ipRJ/fdBP9+9jhlt9JVxazcAhAMeiHUZNU7tg8Thsp1WzyO9\nid2A2jMcC/u4tnaXKpIpQWMMO+Qr7MdaoohkrorvXVjUnGOEfkpVCSGDDlbuK9LNGdKU2t0B165d\nwyOPPIJvfvObN33uxRdfxMc//nGcP38eX/3qV418G67RrN0mCWlBEOD3Uk8NoZI0QUizPhVeL7q5\nogipLpuWfA+o9u5UrmqrMViJbAX1hoLFjTw2kiXUpIZm7Sf0o7UNGDy+gj43ypyeQ4Ca2A2YW5EG\n+K16EIfLVroEQH9iN2Mg7EWuWEND5tMqXKxIptm6gVa7nl1dhmvNudoNWcHfPr/Q49XYm0ZDRqXW\nMF6R5l1IN491snYfQLlcxhe+8AW8//3v3/PzX/ziF/GVr3wFTz31FF544QXMzc3pXiTPsPAZUy+8\nfpdtL7qMF95ax//8h8/hh68s93optmY7YzyEy+kQEPTxa0vVEpVNFNJa4NiGfezdiebfGgBeuriB\n3//6q/gnv//3ttoM4JGEScdX0O9GuVaHzKkA0NJgTeuRVu9pdjr+MvkqvvfideSK/Pbg2hWjM6QZ\nsYgPsgLkOfwbNWQF5WrdtMIIAAT8qpjg2c2yH+uJkvb/37+wyO1zhB0oNZ/rg35jApP3SSxMv1DY\n2AF4PB48+eSTGBkZuelzKysriEajGB8fh8PhwEMPPYQLFy4YWiivmG3tBtSDz84V6a9+6038/tdf\nxeJGHt998Xqvl2NrWDVtxEBfGgAEAx5uK0tmJnYz7JjcvdM29//9eA4/v7yFqtjAxflkD1dlf8xo\njwDUypKiqGM9eIQ9VIUD5kyQmBhWJ0isbttnjNxfPXsV/+bbb+EffelZfP/CYq+X01dspcwR0ixV\nnsc+aTNHXzHsHiDLKtIP3zuFSq2Oly9t9HhF9qVskoOVBcjymnvDrN1UkT4Al8sFn2/vne9EIoFY\nLKb9OxaLIZFI6P1WXKMJaRN3XoI+Nyq1BrfWp92IUgO///VX8f0Li3j+zTV8/8IipiciOD4ewfxq\nllv7iR3YzpQRDrgNX5BCfje3fwezrLc7mZ5ggWM2EtJNwef1OLUEZgB4e46EtBESJrg6gFYVgdcN\nqdbYHnMeXo6NhQHAVuF3VxYzcDkdcDgc+PO/uWjbgCceYe4oo9Zu5pjgMbmbCRMmVMzA7j3SG8kS\nHA4BH7n/GABgbtU+Li/eMGu0GtvoKXFbkVbXdavMkebmp1xZWYEk8XlQ7MXCgtorkkirDxnbmytI\nJ8zJblMa6g3m8pU5BHzGU4yt5spKAS+8tY4X3lqHyynA7RTwyQ+P4bVrWSxu5PHDFy7irplor5dp\nOxRFwXa6hOEBr3a8HUS71zlRR1VsYHZ2Hk6n/rELVjC3tAkAEEsZLCyY83DFHqCX1lMd/+56zfzy\nNgDg3lNRvHApjXefiOKdpTx+fnkdjy6Eerw64/Tq77CykQYAFDNbWCjq39B1Kuqx+dY78ygf4e/v\nkcoU4BCAjbVl3WO+bqCm3o8vz29iYcGcADMrqUkyFjdyODYWwETMhxcupfHTl9/B8bEApLoMl1No\n+3uxyzWil2wkCgj6nFhbWTL0PtWyKsQWltYQ85YOePXhsrytbhbUxbJpx0StlAUAzC+uYSzUfRW+\nF8fmdraGb/90Hb/5S0ewvJlDPOyGs56BQwAuzm1iYSF46GvqB+ZW1eq+WCka+rtmm8WHtc1kT69d\n7b73yrq6+Z/PpbCwwKeDSw8zMzN7ftwSIT0yMoJkslVF2dra2tMCvpOpqSkrlmIJCwsL2i9UFlbg\ncTlw+tRJ095/OJ4BFgsYHjti2EZ1GFy4dgWAaikslEV8+r88h/e95wRC0SS+/+o2tvLOtgcg0Z5c\nsQaxfhGTowMd/f52Hpe7GY4nMbtWwsj4JKIhvh6KxedTAIB3nzupzRk1A5/nChTBZZtjr/qMapn7\nH8/fj+kL1/HR9x3HH/771/DGtQRiw0cwEObr79YN+x2bVlOsXUc44MFtZ4xdo+9IOPHD1xNQ3FHM\nzBwzaXXmUVcWEfR7cOLECVPeT1EUhAMLSOYbtjiHLs4nISvAu06P4+TkAF64lEa25sWlNeDP/voS\nfB4nHnrPJP6n33j3DV/Xy2PTTlTEK4hFA4Z/V2s5L4B1BEOd3dcOk5y0DWAek+NDpq0tX98GfrgK\nly/S9Xv26th85dmruLJSxEvXqihVG7h9egi3nT6Jo2Mr2EiVcOz4NJwG5iDfqmwW1wFcx9TEiKG/\nayBaAjAHp8f4+aiX/Y7NV+YlABuYPnoEMzP7a79+wJLxV5OTkygWi1hdXUW9Xsdzzz2HBx54wIpv\n1XPMmAm3m1bKoz0q9O9cV4XQHz/xS/j9z3wQv/agenKdORaD1+PEm2RN1YXWH23CZkqrp4a/Y4rZ\nmM0W+AGfWwsDtAOJbAUDYS8iQQ/OP3IG0ZAXd50cAgC8TX3SulAUBclsxZQgu/EhtQqzkeSzZ7hU\nEU0d2yMIAo6Nh7GRKtliBNa15QwA4PTRQZydiQMA3p5P4a9/Ot8cK+nAs68sa/17ROc0GjKKFQmR\noHHLczDAb+Jw0YIeaXZfyxb46wlvx8pWAQDwo5+rYbETw+q1b+ZIFFWxgfUEn9dA3jErU6k1R5q/\ncwigsLGOuXjxIh5//HF85zvfwV/+5V/i8ccfx9e+9jU8++yzAIDPf/7zeOKJJ/Bbv/VbeOyxxzA9\nPW3aonnCCiEd8NtnXEK9IePKUgbHxsIYGvDj7Excs8+5XQ6cnY5jZavAZbAI72g9aSaEcAU5HmXD\nziGzd7iDHPeF70aWFSQyNwu+O0lIGyJfElEVGxiJGT+HWPjWepIvOyqjWDE3bRgAjo1FoCitB2ue\nudoU0meODmJowI+xeACvXdnCdrqMB++exEfffxyyrODKYrrHK7UfhbIERQGiIeNCmufRPVoPq0mB\nfQA0J1GuyN+9tx3sfK831JyeI81r38nJAQDA/Gq2NwuzOWaNyw14XRAEChvjBd0/5blz5/CNb3yj\n7efvu+8+PP3003rf3hYoioJSRdIqFWbBhpjbYVzCwloOotTAHc0KwG7OnYjj9avbmF3O4P5z44e8\nOnvTGttjRkWa44eXsmhqBYAR8ruxlihCURRzekYtJFesod6QbwrEOjk5AI/LoVXbiO7YSrOkYePX\n6MGwFz6PExscCmmp3oAoNUw/j442A8eWN/PaQzSvXFvKYCDs1c6hczND2EypFbVH7z+KcrWOb/1o\nFpcWUrj7TP/bDc0kX1JdQ5GgcdcQz6N72EazmedRJOCBIABZDsd97UVDVrC2XYRDAFje7UTzGffE\npJp1M7eawy/dY592TF4wK2zM4RAQ9PFbKLjVwsYssXbfKtRENVnbsoo0pyfJTi4tqLbuO6b3FtJs\nk2Frx4xcojPMmCHN4PrhpSKZakllBP1uyLKCmsi/LZVtmuwec+ZyOnBkJITV7SK384t5ppU0bPwc\nEgQB40NBbKRKUBS+/hbsvLaiIg0ASxt8V6RTuQqSuSrOHB3UNs2YvfvIcAi3H4/h9uMxNSypec8i\nOifXnCUeNcPa7WObuvxV06wYf+V0OhAJem6YxMAziUwZYl3G/efG4fWoYbfMjTM9EYUgAPNrVJHW\ng5nHVyjg5vJ5Dmi5aW+VijQJaQOwinHI5D6AoI9VpPm3drP+6LNthDQTBtvpyp6fJ9pj1gxpgN+K\ndL0hoyqaX0kDWruhdnB2sL/1Xr28U6Nh1MSGJraJztlmFWkTziFA3RisiQ3uWlWs6O0EWhVp3kdg\nsQ3d2463xm7ec/sIjgwH8YlHT0MQBAT9bkwfieLqUgaiDXq+eSLfFNJm9Ejzei8CzKsY7iYa8tqm\nIs1s3Scmo/iV9x3DyakBDEXV+5Lf68LkSAjzqzna2NWBmeNyeR5pWqnVIQiAz3NrCOlb46e0CLOC\nA3YTsEnYmKIouLKUwVDU17ZqylLHt6ki3TXbmTI8LodJfWksbIyvKgDbUTVzbicjuOOBLR41b0a1\nFeznPjg6qoqZla2CLVL8eYJZu80I7AOAiaFWnzRPx5QVlTRAncQQDXm4tLPv5M1ZNUPgXaeGtI8N\nhn34k9955IbXnZ2JY341h2vLGZw7MQSiM/JNERgxIRDS6XTA73VxWU3TNqRMdkgNhLxY3ixAqstw\nu/iuX61sqUFiUyNhfOCuiZs+f+LIAFa2VrGZKmmVaqIzWPipGZoh5PdAlBqQ6g24XXyNya1U6/B5\nXHDcIsnufJ/RnGPmSbGTVmo33xXpZLaKbKGGU0cH274mEvTA53FiK0VCulsSmQqGB/2m9Pfyau0u\nsJ40C6zdTFSUON213cl+/fCTO4Q00R2akDapIj2hJXfzJSytqqQB6v2ozHnS9VtzCQR9Lswc2b+P\n+1zT7v3j11e5s+fzjJkVaaBpS+XwulyyaGN3IMQCx/ivSq9uq/eZqeZ9ZzcnmlkJcxQ41jWlqgRB\nMMfyHOT0mQ4AyjXplumPBkhIG8KsBL7d2MWSOruiBiCdmmr/8CIIAkZiAeqR7pKqWEe+JGLYJAHA\nq6i0qpIGtDakePuZ92K1KZL3qpweJSGtm+1MGSG/27RrNMt84G38i1XWbgDw+1yociykt9JlbKbK\nOHdi6MDk/7tPq3bvZ15awl/94OohrdD+5E3skQbU47TEmTsKUB1bXo/T9KoxS+62g717easAp0No\nG6LLAsfmV3OHuay+oFSREPC5TanU8twiUanVSUgTnWFVFUCzdnM+A3d2Rd2RPD3VviINqNWgUkXi\n8oTnFdaDGY/6THk/NneQPRDxgqWVNLZ5wLmzoyY1cOl6GsfGwntWfMaHgnA6BCyTkO4KRVGwla5g\nNG6eHZ5ZGTdSfFWkWxtS5rdI+L0uVMUGtz2Rb80mAADvOjV84Gt9Xhf+xT99AGPxAP7DD67i+jqJ\ngU5go5vMSO0G1OO0Umug0ZBNeT+zKFYkSzajWrOk+RbSiqJgdauA8aEgXM695cHMRFNIU+BY1xRN\nHJerCWnOKtLqNKP6LRM0BpCQNkQrOMDcAybot0dFmo3kObFPRRpo9UknqCrdMeyGO2BCTxoAhANu\n+L1OzerKC9q4ERPndjLsUpG+tJCCKDXajuRxOR2YGA5hZatAdtQuyBVFiFLDNFs3oI7A8nqc2Exy\ndh41q3tWbEixwJiqyOeG1Ftzan/0Xac663mOR/34+MOnAbQ2g4n90cZfmZDXAexoNeLs2lwsmyd0\ndtKaJc23kE7nqyhV621t3YB6jZkYCmJ+NUf3oy4pVSTTwonZMxNvOiFfElFvyFxliFgNCWkDWBU2\n5vOow9YrHNvpZFnB3GoWR4aDB+7gsgdZ3kQcz2hCOmxORVoQBIzF+RvdY6UlNcipnX03v7i6DQB4\nzz6zbadGQyhX69ylRfPMVlqtGpsZ0CYIAoaiPiRzfCWos7wOK7IGAs3KAq/3o8uLaUSCHq0FohOO\njdsjjZwXciURPo8TXrc5oUY8thrJsoJy1ZqK9IBNKtLza6pD48SR6L6vOzE5gGJFome6Lmg0ZFRq\ndQsq0ny5DM3OJbEDJKQNYJWQdjgE+L0urm4yu1lPFlGu1nHqAFs30HqQvb6Ww//+b57HT3+xavXy\nbA/buR4wqQIAtEb3ZDi6mVsrpJvODo7PIwB4/eo2PG6nNvd2L6aoT7pr2Mg9s2/o8agf+ZIIqc7P\nCCXN2WFRjzTAp5CWZQWpXAXjQ8GuQhmZ6F7aICHdCfmSaEpiNyPIYX9npVaHrFjTHmGXHmnW98wC\nxdpxkvqku4YFNrLnEqOwNjCenueAnWNbqSJNdIAWNmbyHGlA7ZPmefzVO9fTAPYPGmOMxNQT6js/\nmcfF+RReurhp6dr6gVZF2ryHl/E4f4nD2vgrCypprR5pfs+j7UwZy5sF3HkiDs8+1Z7j4xEALRsr\ncTAs4NDskWGxZm5BOs/PA4xVwZdAy9rNo5AulEXUGwpike6cOwGfGyOxAJY2aWPqIBRFQb5YMy2x\nG+BzioSVEyS0HmnuhbTa6nBgRbqZjk990p1jduHtSDOvY3Wbr+BLs0dO2gES0gawtJrmc3EbkvT2\nfBJP/vXbcDgEvPv0wQEvozFVwLEHMd77hHggUzTX2g0AY00hvclRUBLr7bRkjjTnPdKvX93G73z1\neQDAfXeM7fva++4YQzTkwXdfXOR6g40nti26oceboi3Fkb2bCRIrhDQLjanW+KnAM1irQ7dCGgCO\nj0WQLdRQ5DzUs9fUxAbEumxaYjfQut4XOUrubrnAzNu8ZmgVac6qh7uZX8shFvFi8IDziSV3X13K\nHMay+gKzhfTEcBAOh8CdS23bog1sniEhbYCyhYnDAZ8blarEVT8roO7a/l9//hLqDRm/8w/vxdGx\nyIFfw4KuGLwlR/MIu6lHTbZ2A7dgRZpDIV2TGvjSv3sF6VwVv/HLp/Ar7zu27+u9bif+wQdnUKpI\neOalpUNapb1h1Z9BE10dQKsincrx069eqkrweZxtk3aN4Oe4R9qIkGZ90hspfv6OPJIzeYY0wOfo\nHiZyoxYIaa/bCb/XxXURIVesIZmtHDiLHVCDrmYmori8mEZN4m+DjUeYa8issDG3y4nxeIC7EFIm\npM0a3WoHSEgboFSV4HY59rVk6iXgc0FWgKrI10VqLVFEVWzgsQ9M4/13TnT0NYIgYHwoBJdTQDjg\n4fpmwgvZQg0OwbxxI8AOazdXFWn15hKwoD3C41bngfJo7V7bLqImNvDo/cfwDx+7oyMB9NgD0/B5\nnPhPP53nbmwMjxQs6htmaaQ8Celi2ZqQJADaJmiZRyGd0y+k2SbwOgnpfWGJ3WYKTB6t3dnmiC8z\n26l2MhDycl2R1oLGJve3dTPuOjUEqS7j8vWUlcvqG6zIVJoaDaNYkbhqGdhOlxH0uSy7H/EICWkD\nWDUqAWjZUnmzcWaafYHDXQYJ/PYn7sYX/ocP4MhwEPmSyNUOGo9kCzVEgl44HZ0H6BxEfMAPl1Pg\nytpdqkgI+lym/pw7CWO9r7gAACAASURBVPrdXFak2UzobpKGwwEP3n/nOFK5KlebIbxSLDePLZOr\ntPEof9bukonzSXfTsnZzKKRZRTqqw9rdzB3YSJOQ3o/WDOk+r0gX1ePACms3oLrLchw/+7T6ow+u\nSAOtue1vzlJuRyewjZqwiecRbyGkiqJgO1O+parRAAlp3SiKglS+ipiJPaw7CXBqS80WmjebLn/u\n6Ykozp0YQiToRUNWuO3/5oVcsWb6zrjTIWA0FsQGRzNwi2URQQtmSDOCPrc2GognVnUIaaB141zn\nyJ7PK/mSaOpDCyMeUTcReRlFJssKSlXJklnsAN/W7pQBa/eR4RCcDoGs3QeQ16zdZlakmz3SHI3u\nyVlckQ4HPZBlhcvzCNiZ2N1ZRfrsTBxOh4A3ZhNWLqtvYBuvcR2bfu1oCWk+AseKFQmVWuOW6o8G\nSEjrplSRUBMbiA9YI6SDzZEjZc4EJ4va19t3yHp+8xxZUXhDlBooVeum9kczxoeCKJRFbioBxYqE\nsAX90Yyg38WltZtVpKfGuhPSE0NqUidPfe68UiyLCFsgLgcjXggCP9bucq0ORbFmegQA+DgW0kas\n3W6XA6OxAJJ5fsQcjzBrd79XpHMF83NJdsJ+5gJHdnaGLCt4ez6JWMSH4YHO3IZ+rwu3HY9hfjXL\n1YYIr7BrFWsNMoOpEb4q0rdiYjdAQlo3yeZJMdThRadb2O4vT70PgHEhzW7GbPeXuJmslh5q/ibN\nWFy9wG1yIMTqDRlVsWFpL03Q54ZUlyFyFoiyslVA0Ofq+jxigXHrCT52oHmlKtYh1mVLhLTL6UA0\n5NUejHoNcy1ZEdgH8F2RzhSqcDkdujfjBiM+lCoNNGQ+7bY8kLVAYPIYBJktWhc2BkC7FhU4FJ1z\nq1nkSyLuuW2kq3ns7zo5BEUB3p6nPumDMOKeacfkiLqxzouQ1iZl3EIzpAES0rpJZlWbxpCJu0s7\n4TEZFgAyzYvBQeMR2sFuUrkSXxsEPKGN4bDAYsYCxzbTvRfSWmK3BaOvGDw+sEl1GevJEqZGw109\ntAA7hDQHGyE8w44tK4Q0oNrzUrkKF/2OrBpkdY80j0I6nasiFvV1fR4xoiEPFLSqrsTNtNLvzRMA\nLqcDfq+Ts7CxGsIBtyXJ90DLzl7i6GdmvH51GwDwnttGuvq6247HAACzKzQG6yDSuSoCPpd2PTUD\nn9eFkUE/Vrc5EdIZVReNUI800QmakLbI2s36KHjpw2NkCzW4nILuKiLb1aaKdHusqAAwIs2NjAIH\nI8i0GdKWWrv5sxCuJ4uQZUXrb+oGv9eFWMRLQvoAWNXHqraBeMQPsS5zsUHDjm3rUrv5FNKyrCBd\nqGlzvfXAgqXoftQedj8ye2M36PdwNUc6W6hZVo0Gdli7OfqZGa9f2YZDAN7dDBDrlBOTajAZ668m\n2pPKVU2tRjMmR8NI52tc3IvY6CuydhMdkcwxIW1NRZo9HPCUDAuoVrqBsP4KALOsUwWgPVmD9vn9\n4Kk3zWoBALT6Rnnqk15tBoMc7bI/mjE+FEIyU4ZU58uuzhMsIMmKsDFgZ3J37zc62aaBmT2sO+FV\nSOdKNciyYujhlAlpFqJJ3Ey2WIPX4zS1kgao130e7kMA0GjIKJRFy4LGgNamHm890sWyiKtLaZw5\nFus6sDAS9GAkFsD8WpYLdw6vSPUGCmXR1KAxBruG8dAy0OoDt6bAyCskpHWSyjZ7pG8ha7eiKMgU\naoYEHnvYy3NQEeUVrUfagkR4nuZ3sjVYZUnd+d5ljpK7WdDY5Ig+IT0xFISsAJspftLXeUNrG7Cq\nIs3R9bmVqmyNkPZp46/42rhhD22DEf33IyacslSRbksmX7NkJFQ44EG5Wke9IZv+3t2ijuS0rj8a\n4DOpHFDHV8lK97ZuxsnJKHJFEcls76+FvJIyEIp4ENozDgfBxKxgcSvNkAZISOuGWbv1zK/sBJ/H\nhaDfzZW1u1StQ6rLhnqltB5pzkLUeKIVNtbnFekys3bfWj3SbPSVHms30OqTpuTu9uRZldaiYyvG\nkWPIaiHtdAjwuJ2o1Pg5h4BW8KWRh1O6H+2PLCvIFY1tnrcjHORnU1frA7dUSPPz8+7k8mIaAHDn\niSFdX3+yae+ea86hJm6GPcebmdjNCDQ3Onlw3ZUqEjwuB9wuZ6+XcqiQkNZJMldBOOCGz2Ou3Wkn\nsYiPi4oHoxU0pv9mE2Wp3VSRbkurR9oKId3cFeegT4vNEmej3qyAbRzkOaoCJHMVCAIwpHMTbmJY\nTepcT1JydzvYJo1V1m62gZrmwBJsxZzf3QS8Lu6s3SkTbIRRzdpNQnovihUJDVmxxPLMU4o120iJ\nWmrtZvfe3guenVxbzsDhEHDiSGfzo3fT6pMmId0OKyvSAR9z3fX+uCpXJQRusWo0QEJaF4qiIJmt\nWNYfzYhHfShVJFRFPh5gzAgd8Xld8LidZO3eh9bv2XwRwNOuOHswD1g0/xbYMbeco+Mt0wy1cepM\nh51oVqSXNwvUl9YGrUfaooo0czpUOLDT5YvWVqQBtU+6wpu124RxMqzSShXpvWG941a0GfHU5qXd\ncw8jbIyDjQNGvSFjfi2HY2NhrYWjW6gifTCtirQV1m5Wke79vahUqWu5NLcSJKR1UBHV+bdW2DR2\nwltyd6Z5UzU6BiMa8iBPDy5tSeWqiAQ9lthjXE4HfB4nF7viTEibHWKzE1Zx4ul4y+SriBk4h8bj\nQQgC8Owry/ivf+97uHw9beLq+gOrx18xOx0PfWksuNGq6jsA+LxO7irSZghpdn3IUEV6TzKWBl/y\n0zPMeuQPI7Wbh01sxvJmAaLUwOmjg7rfIxL0YGTQj3eup/DHT/8C15ZpFNZutIq0BUKaFSIqPFi7\nq5Im7G8lSEjrIFtUD1irK9KtPjxehLQ5N9Vo0EPW7jYoioKExW4HXtJSy80Lf8BCa3eEs1aCclVC\nVWxgwEB7hM/rwmd/8268+/QwShUJb84lTFxhf2D1+CvNTseDkC6L8Hmc8Lqt60vze12oinWuHBBp\nE+ySAZ8LLqdAFek2WDX6CgAiQX4qtFrl3UIh7XQ6EPC5uGirYjDRe2pKv5AGgPffOYFKrYFnX1nG\n1//uHTOW1lewLI14xIIeaR8fFWlRakCqy1SRJjojpwlpayPeWcU7zYuQzptTkY4EvaiJDW4s6zxR\nKEsQpQaGrRTSAQ9KHDy8HEZFmvWN8vKgzB5MjVSkAeCR9x7FP/7YnQCARKb3gVe8USiLcAjWtQ2w\nh5cyBwFcuaJoqa0bUM9RRQFqIj/27nShCo/LYSj1XxAEhPwubq4PvGFl8CVzi+RLfJxDgDUbBjsJ\nBTxcjb9iQvr00QFD7/Pf/9o5/NUXH8PEUBDzqzQKazfpfBWCYCxfqB1BbVO3t8cVCzujHmmiIzJM\nSB+StZu7irTBi0GE9a3SyJGbYGnwVgrpoN+NUrWOhtzbm91hCGm3y4Ggz8VFHx7QsqOacUNlx0gi\nQ2OwdlMoiwj6PXA49M27PwgWMslFRbpkvZD2cThLOp2rIhb1QRCM/Y3DfheyhRo9/O+BlRVp1orA\nRUWahY2FrD2PQn43F1Z2xuxKFl6PE0d1TpDYSdDvxsmpAZSqdWyl6Z60k1SuimjIC5fOXJT94KUi\nzSaj3GqjrwADQvpLX/oSzp8/j0984hN46623bvjcww8/jE9+8pN4/PHH8fjjj2Nra8vwQnki19xB\ntXrouGbtzvNRcTIrkCParBL+4b9/Df/2by4aXlc/wUSR1dZuoPc7mEyEWGntBoBIyMtNxSmTNz6y\nh+HzuhAOeJDI8nF94IlCSdKso1bgcAhqAFePH16qYh2i1LA0sRto9YTzIqQbsoJsoWrKeRQOuCDW\nZW5+Np4wKxdlL3hK7c6XanC7HJZu6gJqq0lVVC2wvaYq1rG8mceJI1HdwZe7OXGEgsd2oygK0nlz\nrlV7EeTuee7WE9K6rhqvvPIKlpaW8PTTT2N+fh6/+7u/i6effvqG1zz55JMIBoOmLJI32M6PlcEU\nwI6wMW4q0lX4vS7d6Y6M0VgAgDq/8PJiGr/1K7cZfs9+gVWkLRXSO5K7rQpj6oRKrQ6XU7B85mA0\n6MF2ugxFUQxXr4xi9oPp8KAfa4kiFz8bLyiKgkJZxFg8YOn3CfhcPbd2Wz1DmuHnTEjnijXIijkb\nUqFmOE62WLslHwL3w9KKNEdCulSpI+h3W34NDQVa4yet2Jzohq10GbICTJlQjWacmFRHaM2v5vDB\ndx0x7X3tzOxKFjWxYUrVfy94yetguTsUNtYhFy5cwCOPPAIAOHHiBHK5HIrFW2emaamq9omx1Emr\nGAh54RD4snabkd75kfcdw+f/0fvw0N2TAICV7YLh9+wXEochpDmZJV2p1S2vAADqhldDVjTrUS8x\n09oNqPbumtjgqu+u11RqattCyOJNooDP1fOHl8MS0rxZu80IGmOEA+rPliv0XtDxRrZYg9fjtOQ6\nzYIACxz0SFdqkua6sBKekrtZtsbwoHnPGmwWNc2UbvHcaysAgAfvtmZjwedxwiGg5883rCJ+K4aN\n6bpyJJNJnD17Vvt3LBZDIpFAKBTSPva5z30Oa2truOeee/DEE08cuNO3srICSer9xaUT2DzN5PYa\nChlr28zDARe2UgUsLCxY+n0OQpYV5Io1xENOU9Yy6AFGIqq96bW3F+CUjKVG9guLq2oCc6WQwMJC\nruuv7+RvI1XVjYvZhWU4pd6NqsgXq3A7O1uzEQRZrapcvDKPkQFrXSQHsbKRBAAUs/r+vrvxOtRr\n5hsXZzE5bG1mg1EO6xqWyquCSJBrln5PJxooVSTMz8/3zA1wbVk9l+tiydKftVLKAwCuL60iIOQt\n+z6d8s5icw31suGfO+xXHTFX55fgVUgA7CSZKSHkc1h2bPk9DiSzxZ4/3xTLEoJe635ORkNUW7eu\nzS1CKnXm2LRqTZdnU+r/SOb+/uMRD64tp3t6XeSFRkPBj19bRsjvxIDbumu01+NANm/tPWAvdn6/\nxWV1DGepkOn5+WwVMzMze37clC243SEdn/3sZ/GhD30I0WgUn/nMZ/DMM8/gox/96L7vMTU1ZcZS\nDoVybQ4up4DbTp+w/EIRjy5jI1Vq+wc8LDL5KhTlIsZGBkxbS1mJ4D/+ZB2Vhq/nPx8vVOprcAjA\n3edOd923tLCw0NHvcWodALYRjg5hZqZ39iupcQXDA37L//aTl6vA5QzCAyOYmYlb+r0OQnp2EwBw\n19mTWmCVEU4syfjp2yl4gjHMzIwbfj+r6PTYNAN5JQvgKsZHY5Z+z8HoJha3Kpg6ehweC0dP7cdy\ndhXAIo5PjmJmZtqy73NkQwCwiYHB4Z5eMxjXthYBLOHk9ARmZow9O7x6Vd1M9AYHMTNz3PDa+gVZ\nVlCsXMSpKfPu+buJhuch1uWe3v8bDRli/W0MRoOWr2NqqQG8nkB4cBgzM2MHvt7K6+bzV1RXx9nT\nxzAzM2Ta+952PIUX3lpHJDZharXbjrzyziaKlQZ+9YPTOHXqhGXfJxyYgyS3F3pWsPvYfGOpAWAN\n00ePdHRs9xO6yqkjIyNIJpPav7e3tzE8PKz9+2Mf+xji8ThcLhcefPBBXLt2zfhKOaJcbSAU8BzK\nblvQ71atio3ehlOYNUN6J0fHIgCA5S2ydjOS2QoGIz7Twj/2QrOX9dAKpCjKIVq72ZiV3geOZQo1\nBHwuU0Q00LLl0QisFvlmz2XEcmt373vT2DEdsTivw+9VNwrKvFi78+Zbuyn9/kaKFQkNWbF0JFQo\n4EGhxxMVWLuC1aGXABBkbVVcWbvNzZJgfdILa+TueOHNdQDAh++xtlAY8LlR6fn4K/U8MjKO0K7o\nelp/4IEH8MwzzwAALl26hJGREc3WXSgU8OlPfxqiqF4cX331VZw6der/Z+/No+U472rRXdXzPJ15\n1tEs2bItW/E8JLEDiTMwONc2JBiyWHlwgct91yHAXVzCg4TcCytcLiEJhDxCXgjBMTEksUli4gwe\n5HiSZMuapaMzzz3P3VVd74/qr/pIOpJOd9c3dE7ttbyWJZ1T1UNVfd/vt/dvb5NerhgolFVmFu9k\ncJ+3tT0N986gz4lwwGUV0nWoNQ3xdIlq9BWwxvCEo8lLuaqiVtPgYbB5aWRJ85+BTGZLpt5DRiFt\nOXcbIHn3YcpmPiJkSW9WszEzC+m+iBt2m4yvf/8Mvva9n6ymfzuIp/VnSoSS2zCgN7sqSg2lCr/r\niqXbcMAw+uS/Fi0nC5Al89NniJnsqiDePjxBmhVkdpwWfB4HCmUFNY6RpmRGm0VDSjS09I7379+P\nvXv34qGHHoIkSfjYxz6GJ554AoFAAPfddx/uuusuPPjgg3C5XNizZ89VZd2dBJ1JUzHCyO2YdHfy\nxSr1zdKVQGJ7zGSkAWCkN4A3zq4yYydFRipbglrTqBqNAQ1Gmqc5BYsMaQLCSKc5M9KKWkM6VzHV\nJdXKkr4UxJyRdjwhaQLxZaTZFtI8C561iJtoNhb2O/CJX78Nf/6Pr+HL3z6B/bt6sG0o3PZxOx2T\nC/ocOi23YWCNc3e+appKp1kQlQULs7GGU7kAjHSqiGjQbXq2MYk3zQgSOckTmXwZfo+DqsIQ0J/P\nmqY/n3klD+SJ2dgmZKRbfnJ85CMfueDPu3btMv7/kUcewSOPPNL6qxIYxbKCmsbuYvEJUPQAaxhp\nk7vTI316IT2zlMWOkc1tOMbCsRtoXFM8pd0kf5fF5qWxsPNlAUiUTNREpjQScMNukyxGeg0Ik0a7\nkPa69PuIZ5Y0q0KaqDoI288byWwJLqfNNPZjz5YY/tPbt+OzX38D04tZq5AGMFUvpMf6g9TOEfCR\ntajCbZ6WuA2zUEcZ0ZOcEzNUtYZ4uoSdFPZcQaNxzZ91541MvoIAAwKMOGXnixwL6eLmde2m2yb5\nCQSZbSEPRNogUUW8C2laeZLGnPSiJe8mGdK0NxRrc6R5gbAATKTdZGHnXEjTaEbJsoRYyGPNSK9B\ng5Gmex8Z0m6Os2lkvpR2HjyRay4mxFA+JNIlRINuU31K+mK6i/JSPG/aMTsZkwwKaeJjkOFYdLGU\ndpP9HO/Ir3imhFpNo7LXCPnJKNXmZqQ1TUMmX2GiJPV6+I8ZFUoKJImNylA0WIV0k8gW2GxcCMiM\ndI6zkQANszGgIRuz5qTZFQAi5EizlXbXF3bO0m5a4xHdEQ+S2RIqVdXU43Yq4ukinHbZmEekhcaM\nNF9G2udxmC7PvBg+jwMBr1OIIlNVa0jlyqbIuteCFNILArxHETC1kEEs5Kaax+43pM48C2l2s53h\ngP5+SVOVFwyjMQrqt4AAzRERUCwrUGsak0KasMCFIr+1KF/Us9hlefNFnlmFdJMgclhWZmMizLMC\n+oNfkhpFiVkY6asX0ov8s0l5gyw8YcoOvA67DJfTtmmk3S6HDW6njbu0e7k+x2y2dH/7cASaBnzl\nOydNPW6nIp4uIRbyUE9VINJu3q7dtN3JCfq7vFhKFKFyNLQBgFSuDE0DYiYX0t0RD2RZwmJcDNad\nJ3KFClbTJYxSZKMBGLJXns7dBYZrkcNuQ8DrFKCQ1q/xnqi5jt2Avr/wue2bvpBmNXYDNJpAeY6E\nW75U3ZTz0YBVSDcN1tLuxuwD50I6U0bQ5zSd+Qh4nYhYzt0A2D54/R6HINJuNvdR0O/izkgTpqu/\ny2fqcR+6bwcGunx44odncejksqnH7jQohK2kPB8NrDUb4yunI6ol2uiL+qCoNWMGnReIcsdsvw67\nTUZ32INFi5FuyLr76BbSQQHMt4xCmlEREAu5keDsaE08NWglhAT9rk0v7c4wGrsB1kYxciyki1Vu\n89m8YRXSTYLIYYk8ljZEMRtLmRzbsxYjfQGsJIvMHwJEeiMKjExYVoX0JnHtBoCQz4l0rgJN4/d9\nL6zqG/QBkwtpr9uB3/nATZAl4J//45Spx+40JDN1tpJBIU1YAF6RULWahlJFhZvRPdQb09mrJc6M\n7dxKDgAw0G3ufQQA/TEfktmyMO7kvGAYjQ3QZqT1/Q1XaXd9rpQFIw3ooz35ksL1GiPS7h6TM6QJ\nQj4nMnm+6y1vsCRGfJwTJGo1DcWyYjHSFjYGwuLRnr8jEMFhuVxVkS8pphuNERDDsdnlHJXjE/zw\ntRn84h9+G1MLGaSyZfzKH38XX/jGUarnbAaZfAWSxGZswO91olCqcmskFEtsNy9BnxOKWuOag7uw\nmkfA66Ayc7htOIyh3gAmFzLMsiSJmQrP7MqLQdjSLso+A8BaFoDPNVWuz8Szig3qr88Q82ZsyTox\n1OM3/diiNAt44zwDozFAjHlalmZjAAy1DPHM4AEyZkTL2DTkd0GtadwJIJ5oECN0R/WAhpqCFyNd\nKCvQtM3p2A1YhXTTIJ3TzcRIpygZjREYhmMU56SXkwV89utvIJOv4JlXZ/DSsQXkSwq+++Mp4/3x\nRiZfYZI5COiFpabps3A8wNK1G2hskngV0mpNw2K8YBga0cBYXxDFsmJskmjji08exy/+4bfxc7/7\nLfzDk8eYnPNqYJUhDTSaQLw2L6X6tex22picj1y7vJ27Z5f1MaChHvPzjUVpFvDG1EIGsixRaVas\nBfEDSXGUAbM0GwMa2ecJjlFyK6kifB4HteYBYWFZRWBNzKXxZ19+FQ//wb/jhTfmmZzzasjUndlZ\nmo3lOTV1CyT6itGYkWiwCukmYZiNMYu/4s9IG7E9FKXdADBFKQJL0zT89deOoFjW7fl/fHQBP35z\nEQBQVWr49sHzVM7bLFhFJQCNhzsvJoC1tJuch1chHU8Voag10+ej14LIMIkskyY0TcNzR+bgdtpg\nt8t49sgc9XNuBI0MaRaMNF85XbHC9h4ibO3iKn9G2uu2U2nsNpy7Ny8jrWkaZpZzGOjywWGn26Rx\nu+xwOW1c52nJ/cvqPuJdSGuahpVkgdp8NEA/Amt+NYf/8TcHsRjPo1Cq4vc/+zyeOzKHXLGK//3V\nQzg/n6Zy3mbAclTPWIs41QnE5MxipC1sCKzNxjwuO2SJLyNtxPYE6Uq7aRmOvXZyGYdPr2D/zh7c\ntm8AC/E8Dp1cwmC3Dz6PA/9+cJJ7dFAjc5C+DAhY0zHmtIFh6doN8C+kyXw0zUKaOOxOMiikZ5dz\nWE0VcWBPH3aPRrl4HKwHlow072uqVK5LuxndQ7GQB3abjMUEv0JaVWuYX8ljqMdPxZW9jzQLNjEj\nncqWkS9WMdxrPuO/HsJ+F9IcVWFFxtJuYpKX5FRI54tVFMsqNVk3AIT8ZH9Bp1H/vZenceTMCn7w\n2izOzaZRKCl4521j+P1HDqBcUfHJL73C3f+GrWt3XdrNaS3KG4y0VUhb2ABYm41JkgSfx8HV1j5V\nZ6TDlBhpv8eBaNCNaQqMtKZp+OrTeizQr7xnL269ph8AUNOA268bxE/fMopUrowfHZo1/dzNIF9S\nUGOUOQg0Osa8GGnW0m7eRQ9x7DbbaGwtiMMui0L68GndHfyGHd2GomRGAOf9VYaMtM0mw+20cWsg\nFBlLu22yhN6oh2s81FKyAEWtUZF1A2vk65u4kKY5g74ewn4XUhyNIPOlKpx2GQ47m+1wjDMjTRy7\naRmNAY254AylpIxjE3EAwKmpBM7MJAEA+7Z14bZ9A7j12n4srOa5NSoIeJiN8SLcyHkt124LG0Ku\nyPahC+hdHp6MNJFc05QCjfQFsJoyn9U6fGoFp6dTuPXafoz1B3HT7l7YbTqTcfPePtx/+zhkWcI3\nn5vg6jDJUgYE6K6aALsZpovBTdrNSYZrMNIxepvT7ogHXredTSF9agUAcP2OnjVZ8PwL6Xhaz7un\npZ65GF63nZu0u8RY2g0AvTEfMvkKt+YB7SLP53Eg4HUa9+tmxAzFGfT1EPK7oKg1bvdRoaQwLQAi\nnAvp5brHAc39XEPxZv7+olxVcXo6BQA4NZU0/n/7cARAw+dgNcU3po+leazH7YAk8RsBLVbU+uuw\nZqQtbADZQhVeNxsGgIBnIV2raXjx6DwCXgd2jkaonYcGq1WrafjH75wAADx0304A+mf59gMj2D0W\nxbahMLojHtyxbwCTCxm8fmbFtHM3C5aZg4Ce8wgAGY7SblkCXA4295KHc1QRrQzptZAkCaN9Qcyv\n5k0fVUhmSgYLUFVUHD23iqEeP7ojHoz00h3NaAaJdAlhv8v0vPvLweNy8Cuky2xduwGgN1p3teZk\nODa7RJ8tHe71YzGeN1zRNxvIGsyKkSYyYF6GY8VylWkBEK03+X6SGWnyndJQvJ2eSkJRawD0wvHV\nk0sIeJ3oqUvVY2G9UbHKOe8+W2BnHmuTJUQCLsMjhDWI8aWHkTpKNFiFdJPIFyrwuhgX0m4HShXV\neHiwxKmpJBKZMm7e2091c2psxk1ktZ5+aQpnZlK46/pBjA+GjL//zfdfjz/7rTshyzoz/b67twIA\nvvHshGnnbhYsZUBrz8OTkda7qObPOa4H7tLu1Tw8LpuxwaCFsYEgajXNdJn13z95DL/3mefx+ukV\nvHZyGeWKiht29gBYYxbIgAm/GuKZkhEvwwI6I81X2u1huB6F6pJN4hXCGjQduwm2DIRQ09hfz6pa\ng8phjb8YzKXdddM4XukZOiPNrpB22G0IeB1IcIq/Wq5nSFOdka4/J9IUpN1vnlsFAFy/vRsAUK6o\n2D4SNvYShGkXgZFmRYwAQHfEi9VUkUscJVFHuRg2dUWCVUg3AbWmIV9S2BfSHCOwDh7VowRu29dP\n9TxGBJZJBUA6V8aXnjoOj8uOD7137xV/dsdIBNuGwzh0cokbC5HJsS2kjYWOEwtQKCtMJaleo5Bm\n//1qmoaFeB79MToGSWtBcl/Pz5tbBEzWj/e5J97A577+BmyyhHsPjADQn09dITd3RrpUUVCpqsb8\nPwt43XZUlBqqCvsCiGxeWJmNAQ2TzSyn2LzZ5RxkWaIaI7dlQG+6mn0PXQziPPzysUVomoY/+NuD\nePSvnuU6YgQAyi0K3gAAIABJREFUs0tZdIXczOTOYcoOz1eCWtNQqqjwutjOdkaDbn6MNOUMaQAI\nEkaagrT7zYk4JAn42Xu2GX+3fThs/D/xx1hN8ZuRbpjHMiykwx4oqmak7LBEiUi7GddGosAqpJsA\nKWRZXyxkxoK14ZimaTj4xjy8bjuu39FN9VzDJs5ZLiUK+O+fewG5YhUf+OldGzIe2jkSQU0DZjjN\nebJmpGlKrzaCYqnKtJDmyUhnC1WUK3RdUgnIhuLkVKLtY/3tE2/gqRfOo1bTMF+fGZ1bySGRKeHh\nn9p5gcpjpC+IeLrENaaPdTMK4JtP3jAbY1hIc45jXIzn0RPxUPUo2TJAmlH0InSWEwX8wd8cxJEz\nK/j8vx3FmxNxvHkujnOzaWOEggcKpSpW0yVm89EA/aikK6HIOEOaIBJ0I1+scmncr6SKsNskanGm\ngP5McjltpjLSmqbhh6/N4MRkAqN9QVy7rct4DuwYbowddgnASDfMY9k1dYlUfyXJ/n0TaTfLpq5I\nsArpJkAcu3nMSAPs5XQL8TyWk0Xs39lDPU/S73EgFnJjerE9FqBUUfC7f/0cphezeM+d43j3HeMb\n+r0xIzqIT/5gw2yMzYPX6bDB47JR6RhfDZqmoVhmK6fjWUgT91CSH0oT4wMheFy2tjfjuWIVT75w\nHk/88Czi6RIqVRU37OhGX8yL63d044G3br/g5w2PA46GY6ybUUDjuuIh726wABwKaQ7SblWtIZUr\nU3dkH+0PQpboFdKapuGT/98rWEkWMdDlw1KigL/4ymvGv3/vlWkq590I5lbqsu5eNrJuoMFIpzis\nRQUj+optARDlGIG1kiwgFvIYo220EPI5TTUb+8fvnMSn/ukQJEnCg/ftgMMuY9uQ3jhey0iH/S7Y\nZInrjDRr81igoTBYTrL3rzDGjCxpt4WrweOyw26T0R9l12UC1jDSjFkAMrNEU0a3FiO9AaymS229\nz9nlHOLpEt520zA+/DPXbnixGCMsBKc5T6MIoDxDuxZBn4vKDNPVUFVqUFSNLSPN0WwsXt8sRRgU\n0jabjF2jUcwu59qaOVxY1TfUy4kCTk3r7PaO0Qg++9G3448/fOslBipkNINXIwrgU0iTc/FQdpQY\nx18BgL8+80eayiyRypWhafQbUi6HDYM9fpyfz5gyb/jUC+fxte+dNv48MZfG2ZkUbt7bh4/96i2Q\nJGA1XcJYfxA9US9eeH2em5fDTN3MjVWGNACEAvwYaRLDyDq2h1zDJPeeFaqKikSmTNVojCDodyGT\nK5s2qvDqiSU47TI++9G34Y7rBgEAv/7z+/DRD950wdoqyxJiITfiHBnpLIe1iCsjXW/quiyzMQtX\nQyTgxlf++Kdxz3VdTM/r4yTtZu0kPVLPwZ1ZyiKTr7RkvELmf4g8b8PnJoUA5bm4y4FXEZDmkN9J\n5itZGnFsFkYaAPaOxwAAx8+3zkrPrzTif547MgcAGOr2w2GX153zJud89cRyy+dsF6xVHQAQ4WiU\nxDpCDmjMSPOQdieMhhT973fLQAjFsmIKu/PPT5/Cl799whi3eObVGQDAO24exUC3H7dco/uPvPuO\ncbz9pmGUKipeeH2+7fO2AhL7NdjFjpE2XLs53EMFbtJuPs8NMjfMYsxouMePilLDN58zx8R1KVFA\nb8xrJAcA+n165/WDl/xsV9iDRKbEzbzP2DtvEkaaRxSjSLAK6SbhZeg0TMDLbKzRVWPTrSXy0INH\nF/Arf/I0/uGp400fg3TjusPNdVy9bgf6Yl5MLmS4mL1k8hXIku7Qzgokv5N1cZmsu5WyyvoF+BbS\nCaOQZvN+SVF7rI1CmsR1AcCrx5cAAAPdl99cD3T7MdoXwOHTy9xcrHk0o4jjME+DF6ZmYxyl3eS5\nEWPQkGoYjrWnsCiUqkas05eeOo6qUsMPX5tF2O/C/l266/2Hf+ZafOg9e/H2A8NGUXDkNJ8oRhKf\n08Wg0CII+lyQJD7xV0TazboACHBSdqyk6GdIE/zyu/ciHHDhi986hv/3m2/iC994E7kWTQpzhQry\nxSp6oxtTR3aFPKhpQJKTEzxxZA8zVBh21xnpZS4z0uzXIpFgFdIdAG6FdIFsTNkUAKSQ/saPzqJS\nVfH86/NNF7UkI7GVjutYfxCZfIVLZzyTryDgc1KfW1oLXrLURL3ooGl2cjHcThskiRMjnSWNAzbv\nd8dIBHabjONtzEkTZgoAKnVH6sErFNIAcOu1A6gqNbx2kg8rzaWQ9uvfKU9Gmou0m4Nrd4LhiMR4\nvZCemGtPobQ2b/vNc3H8j789iGyhgntuHDLiJLvCHvzsPdtgt8kY7PbD6bBheomPMooYNLFoVhDY\nZKmujuLJSLOVdvNqSK0wiL4iiAbd+OgHboKmafi3H53DN549hx8dnmvpWIv1+2gtG30lxDgbji3W\nG9H9DJUdfo8DXredy3sulhVIEuCkaAIpMjbnu+4wEJaStZyOubS7Lq8mY2mrqWLTkToNRrqVQrrO\nQnCYk2YdlQDwc0tNMmZoAUCSJLiddhRLPBlpNptTp8OGHSNhTMylW24czK/oMUNE8hgOuIyG3uVA\nIvJePLrQ0jnbBY9CmpdEE+CT3ely2OCwy1yl3VEGDTiznLvJhvptNw3DbpNxbCIOp13GO24eXffn\nZVnCSF8AM0s5LrLUeKYEn8fBnFkK+V2cCmk+ZmN+D2Gk+fjesGrqXrutC3/53+7Bf/lP1wMAplo0\nkyUNqb7YxgrprrD+/ngZjpFGdH8XG38hgu6wh5u02+20M1frigKrkO4A8Iocyda7pQFG0m6v22FE\nF9x1gy5xe63JmcuVVAF2m9xSlqzh3M14TlqtacgVK0xnOwHdVRMA0owZacLQhhky0oAu3+Mi7U6X\nIEtgmm88PhhCTQNml1tz0V6I59Eb9WLroO6GejU2GtDvn76YF6+eWOQi7+bDSBNpN4dCuqzA5bTB\nxlDFAujrEddCOkT/uREJuhEOuNoupBdW9U3tLdf04Usf+yn8wx++A1/5k3de0cxrtC8ARa0ZkXMs\nEU+XEGPw+V6MsN+FbKEKhXHzwGCkGTcOeHkNGCpDhv4kWwZCuGv/EGSp9XjTpXhzjHRXiC8jvbCa\nh8tpMzw0WKE74kWhpDC/rkoVddNmSANWId0RIIYFWcYFDw9TqAfeug3vu2srfvW91wAAXju51NTv\nrySL6A63Fu1AnLvPzCSb/t12kCtUoGlAwMtWXmZIuxkzAawZWgJehXQyW0I44GJa8AzVC9+5leY3\n4/liFelcBQNdPiMreiOFtCRJuPctIyiWVfz9t441fd52wVpBA+j3EK/5zmJZ5RI34vc6uc5Is2LT\ntvQHsZwstrUpJYx0X8yHoM+JWMhz1dzv0brpZqtFR6solRXki1Wmsm4CXuqoPGGkr6K2MRsNaTfb\nPR0PEyxAV7L0d/kwvdiaB81SQr+PNjwjbUi72XtXaJqGhXgO/TEfc4a2py7ZX2HMSpfKylWfaz/J\nsArpDgDZGLKeZc3kK5CkxlwcC9x/xzh+9X3XIBJ0Y+tQCMfPxzfMblUVFclsueX5n4EuH7ojHhw+\ntcy0Mz67rEeOsJynAdZuXtheV4a8jHG31uO2G3EnrKBpGhKZMrPNPwExBpurX1vNYK0sbceIzkhv\nNA7n5+7Zji0DQXz3x1N49URzTbB2kcmX4fM4jNlTFrDZZIR8LqS4mI0pcHNgAfweB/LFiinRUM0g\nkSnCaZfhYyTDJU2kdljptYX0RkEK6VZlsK2CxPR1MTCiuhjhAJ+1qFBvkvhZF9KcGWmWzUaCkb4g\nsoVqS+qdpSZnpMk1TMzVWCKVK6NYVpnLuoGG4RjrCCwi7d6ssArpDoDDLsPjshsPQVbI5CvwuR3M\npYMEN+7qhaJqeP3MxhxM2412kCQJN+/tQ76k4M1zqy0doxVM1zdMY/3ssjuBRmY1c7OxTAk2WWK+\nmHucdlSqKtPZw0JJQaWqMjVWA4DBHsJIt1dI337dIH77wevx07esP9N5MRx2Gf/3w/shy9IF2bks\nwMNnANCLAF7Sbh6bF7/XgZrG3rgvkSkjGnIzY3nGTHDuXowXEPa7mnKFHq2vA1OLGbx8bBEH32AT\nhUUcu1lI5y8GGTNirezIczIbc9htcDpszBnpbKEKScJV/S5owGgQteBBs5QowO9xbPh1h/0u+D0O\nnK+bBZ6fT+PZw7NNn7cVkPVzgEchbTQQ2BXSmqahVFG5NHVFgVVIdwiCPifzgidb4LMxJbjlmj4A\nwME3NmZeREwWmo2+uuCce3XDpJfeXGz5GM1isr6wkBxtVgjVZ7LTefZmY5GAi6lDObAmAqseG8QC\nvGTsXSEPnA7bBYz048+cxm//xQ8Nk6rLYT6u/85Alx82WcK9bxltynxoy0AIvVHvBc7ftKFpGr9C\n2u8yGiasoGkaihWVS24nD88OtaYhlSszbUiNE8OxFp27VbWG5WRhwwZJBNGgGz6PA2+ei+OTX3oZ\n/+exw0wiGeNp/VkVC7FnpInUmHVhSczGWKkc1oKH10AmX4Hfw4ccaTSILj+yMDGXxn/+s2cuaF5p\nmobleob0RiHLEnaNRbEQzyOZLeGvHz+CP//H15iMDvAyGgMa43os76NyVYWmbd7oK8AqpDsGAZ8T\n2XyFWcaxpmnI1iOZeGHbUBg9US9eOraIqnL1TaoZ0Q57t8bg8zjw42OLzD7rqcUsJGnj8lmzwCP+\nStM0JLNlhDnM4RmFNEPn7kZkD1sZuyxLGOz2YW41h1pNQ65Yxde+dxoTc2kcn0hc8XfnV9rfCPRG\nvEjlyigxYi0LJQVqTeNTSHNw7q4qNdRqGtPoK4IAhwisTK6MWk1j2pAa7PbDYZdxfqE1RnolVYRa\n09DX5H0kSRJG+wLI5CtQVA2FksJE8mxEX3FgpHkZqpLzeRgz0oCu7GDtNZAtVLjIuoFGKsv0RSML\n5apq7EF+dGgWM0s5PP3jKePfk9kyKkptw7Jugl1jEQDAy8eWcGYmBaA1hVaz4FlIk+82y/C6IhnS\nPPw6REHLhfSf/umf4sEHH8RDDz2EN95444J/O3jwIB544AE8+OCD+MxnPtP2i7SgFz0VpYYyIzat\nWNY3prweuoC+obh93wCKZQWHT19d3m1kSLcx42W3yTiwuxerqaLx8KUJTdMwvZhBf8wHl4Ptptjj\nskOSGl15FsgXq6gqNSYRNhfDU2cdimV2i0ySEyMN6IVAuaIikSnh6R9PoVR/dlxtVOLMTApup62p\nuc6LQdgDVlEcPBy7CRrO3ezmpI0M6U3CSLN07Caw2WSM9gcxtZBtyTPDmI/eoEHSWhAZrN2mM4cs\n1B2JOiPdxYGR9hsFAGtGugqPi73zPaAXPflSlZnXgKZpyHEspAe6/bDbpEtm///qscP4tf/5DAql\nKk5M6k3el443iIyGY3dz99HusSgA4GvPnAbhROZbMN9sFkYhHWPreQM0Zu9Z3keNGEZL2t0UXn75\nZUxNTeGxxx7DJz7xCXziE5+44N8//vGP49Of/jS++tWv4oUXXsDZs2dNebGbGSSuIMPoBuG5MV2L\n2+vZtC+8fvU5MeJU2A4jDQD33DgEAPiX759p6zgbQSJTQrZQxWg/W1k3gHpOsAN5Dhti1gwtsIaR\nZjjbmag7DXMppOtz0tOLWXzr+Qm4nTbYbTLeOHv5QjpXrGJmKYsdI5G2NpeEPSAmMbSRqY8nsI6Q\nAxqmeSwZadJQ5SHt9hGjJIash/HcYGxQuKU/CEWt4bkjc03/7kK9AOjvan7U6B23jOKtNw7hoXfs\nrB+LPpNGzMa4MtKMGdp8SYGPAxsN6O9Z08DMALNYVqCoGjeVod0mY6gngOnFrNE8qNU0vHZyGdlC\nBa8cX8LZWZ28WEkWMbmgO3w//7p+7zXLSG8fjkCWJSyvWYPmV+nfR/PxPBx2mct91FALsbuPyH6K\nx1okCloqpF988UXce++9AICtW7cinU4jl9Mv0JmZGYRCIfT390OWZdx999148cUXzXvFmxSsZbg8\n3R3XYsdIBF1hD146tgj1os6tWtPw1e+exMkpvYtJ2K92XUf37+zBrtEIXjy6gNPTdKOwyLzQKOP5\naAIf4zmtpOHYzVHazbCQJiwlL0YaAL701HGspoq49y0j2DUWwbm59GU71mfq1/vO0Uhb5+6pu4cu\nMyukOTLS9WuZpVFSsc4C8JB2+z31zVqRHevBqyH107eOweOy4S/+6RCeen5iw783s5TF48/oZnut\nPNu3DYXx337hRuwa1Vk1FpnS8XQRdpvM5R4i+wyWTV1Ad+1mHX1F4GMcgUXkvqxjNtdi61AIpYpq\nsNIzy1njO3/se6dRVWroqhegz78+j09/7Qi++dwE+mJe3FYnVTYKj8uOLXWfA8KW0makNU3DwkoO\nfTEfcw8YAPC67ZBliSkjTZq6PNYiUdBSC2F1dRV79+41/hyNRrGysgK/34+VlRVEo9EL/m1mZuaq\nx5yZmUG1yj6bslVMTGx8UTUDSllvVJw+NwW5cuUZRzNweiprnJf1e70YW/vdeOlEEi+8chxD3Y0i\n+eWTSfzTM7P4zosT+NV3jeLo2VX0RV2Yn51u+5z3Xh/Gyakk/u5fD+HX37Ol7eNdDoeP6eygWy6a\n8jk3ewyHXMNqtsLsOz51Vi/U1EqW+XVVyOmzjuen5xC00+9MA8D0vO7+nk0uYUJhm0+Oil7ETsyn\nEfTacfM2F9SKDW+eA773wjFctzV0ya/8+IgeWRVytXdNqCX93KfOL2D3gP53NL/vc5P6Z1supJlf\nV6Wc/qycmFrARA8bR/jJRf3zLRfZP59zGX0TPD27hIkJNu93Ykq/LsuFJCYmzG+EXe4ztAP4rZ/Z\ngs984zy++OQx7OzTrrpBXk6V8ZdfP4d8ScW7b+mFVElg4iq+BJdDtb4hPjO5hIkJumz8UjyHoNeG\n8+fPUz3PeiB5zosrKWbXs6ZpyJeq6A45uOxx1Gr9GXl2EoX05Zv/Zr22mWV99K2mmLPXaAU9Af15\n8aOXT0Hb14WDxxr3xcyS/hx96/VRfP25eSP1YbDLjV979wiSK/NIbizAxcBAxI5zs8C1YwG8MZHG\n+bkE1fdeLKvIlxSM9rKvEQg8ThmJdJ7J+ScmJjAxo39vxXyGe61AG+Pj4+v+vSlcvBmmTMPDwya8\nEjaYmJi47AdKC6OLEvDyMnyBGMbHh6ifbzo5A2ASo0O9GB+nV0huBLfG7XjpRBKpiht31T/3qqLi\nE/+kjwwkslV87lvTqGnAr7xnH8bHB9o+5/g48PThJE7NpDA0PAonpfnlb76sS5nect22ts3GWrku\no6EFzK2uYnR0DDYG+buvT58FMIvtW4YwPt5ch7ldnFm2AVhAKNyF8XE2zxtF0x3n9+3dDoedbce2\nb6AK/Ms5yLKE3//lm3HN1i44/XF8++VlLGZk/Ow618ry95cBAHe9ZVdbqoFIVwn4+jmUaw6Mj49T\nf2aS62rr2CDz60pypwFMQnL4mK0LWWUFwDn09XYxX4vKUgLAFJyeALNzp5+PAwBu2LvNdBOfq12b\n4+PAq+fK+P6rM3D6u410hcef0Rm0X/ipXcbPlsoKPvX1Z5EvqfjPD1yHd9461tZrG6tpcNjPIFuS\nqH7WqlpDtnAUu8aizK8nAHW12QlosoPZ+QulKjTtTUTDfi7vefBsFXg9jnCkB+Pj3ev+jJnPzVR1\nGcBZDPd3c3m/AOAJ9uKr35/DYka/nr/xkr7/2TkSwam6Guqdd16DiSUFr51cxrtv34JH3r2n5Zi/\neyt+PHf0Rdx/1y7Ec8cxv5rH2NgWamyx3gw4juF+PvcRAIT8EyiUFernJ9fmUn4ewCT6+3q4vWfe\naGnn3NPTg9XVRs7u8vIyuru71/23paUl9PT0tPkyLRC5FSvJBpnF5jFzeDH2jscAAMcnEsjkK3ji\nB2fxmX95HcvJIu49MIKA14lsoYKdIxHceq15m+ix/hA0je6c5/xKHrIscckcBACfR1+gWM1pNeKg\n2F9XXg7S7ky+Ao/LzryIBvRs1F++fw8+8gs34pqtXQD0UQmPy76ueZ+maTg1lUBv1Nu29D4ccMFp\nl7GUKCCdK+PsPF1JHV9pNwezMUPazSdHGmBnNqZpGt48t4qukLvpKCmzsGNEH3U4Pa1v/AulKv7p\nuyfxz/9xyjAUBIDP/9tRTC9m8e7bt7RdRAO6jwWLKLlUroyaxif6CgBssqSPGTGc7TSirzhJu1mb\n9mXrz0ieSSx9MS+iQTeOTcShaRpOTCbgc9vx82/bBgDoCrnRHfHg0V+8EZ/73bfh//q5fW094/bv\n6sFX/+SduGl3LwbWmG/SAsli53UfAfqYRK5QZZY6UzL8OjavtLulQvr222/Hd7/7XQDAsWPH0NPT\nA79fn8cbGhpCLpfD7OwsFEXBD37wA9x+++3mveJNCjJDxGxGOl+fp/Hxm6ch6I160RXSH75/929H\n8cUnj+GZV2bgcdnwyP178KH37IHDLuND790LSTKv00g2bQtxepuYVLaMsN/JhA1eD2QTwWo2LVmf\ndYzwiL9y8yikywj5+W1cfv5t23HnDYPGn+02Gdfv6MbCav6CKBDVMH2ptj0fDeiO+z1RL5YTBfzF\nVw/hr/9twojXoQGyOeLh6RD0uSBLbM3GSobBC48ZabbOsNOLWaRzFVyzrcvU53sz2D4cBgCcmdFZ\ns8OnVqCoGjQNOHhUV51UFRU/OjSLgS4fPvTea0w7d3+XD7lilern3Xgu82uc+z0OppFq+ZK+5nEz\nGzMaUpvH90aSJFwzHkMqW8bx8wksrOaxcyyKG3b0oCvkxm37BozXONRjThwocYQnZAVNw7EEx5QO\nAr/XAUVll/BD1iIeTV1R0NI7379/P/bu3YuHHnoIkiThYx/7GJ544gkEAgHcd999+KM/+iM8+uij\nAIB3vetd2LKFrzT4JwEGI73JzMYA/eG7d7wLPzo8ix8emsVYfxAffOdu9Hf5EA64cO9bRvG2m0ZM\nl+sQCSFNNiCVKzftRmkmfIy74um6IROJDGIJ1mZjmqYhk69g62CYyfk2igO7e/Hi0QW8cnwRg3dv\nQ6FUxUc//ZxhfHdNXQHSLnqjXswu53DopC4Xn1zItG0EuB7UmoYjp5cR8Dq4ZHfaZAl+r5NJ1i9B\n0TB44cdI5xmxh0fP6Qq3fXVVBQ9sGQjCbpNxuh6J+NKxBePfnn99DvffvgWnp1OoKDXs39UDh928\nxujadSgwQmc9Ttdd70McFWgBrwMzy2y8KwCgUNTXAa+bTwHQaEixZaSDnPd0e8ZjePbIHD7/r0f1\nP49F4XbZ8YU/eAdo+nMR8825lTz2bVtfSt8u4ml+zvcEa7OkWcQjFsuW2VjLn/JHPvKRC/68a1dj\nTujAgQN47LHHWn9VFi4Bc9duQeKvCPZujeFHh2cBAI/cvwc37e694N9pzLz013N0FykV0pWqimJZ\n4VJUEvjdbBnpbLECl9NGbeb8SmBdSBdKfONGLgdy77xyfAk/c/c2/P23jmFqMYub9/bhbTcN4+Zr\nzBmPuLhBNLOUveS+NQMnzseRyJTxjptHYeek7PB7HCiU2MlSSxwjRxx2G1xOGzMm7Y2zeiF97TZ+\nhbTDbsP4YBATc2mUygpePbGEWMiNnogXxybiSGZKeLNe8F9rcsE/ECNMWt6QmJsN0uDkqZ7xe5wo\nV1RUFZXJKIzBSHOTdpOoIrbjerzXI9KonZhPIxZy454bdb8S2lneA116IT2/QpGRFqCQXqt0aDcK\ndiMgOdIsinZRsXnfeYchwClHWgRGGgCu3ao/fPeOx3DjLjYz9wYTQEnaTRisEMdCmrW0O1eoGp14\n1jAK6RKbQtpgeThuTtdDJOjGtqEQjk3E8dTzE/juj6cw1h/E7/7SAVOZNFJI220SFFUzXFnNxvP1\njPk7rmvfZLBV+DwOrFCUrl8MQ07HaS7N52YTm1er6fPR3REPV+UOAOwYjuD0dApPvXAe2UIV77x1\nEEO9fpyYTOC5I3MGc77XJEUHQX+9AKCpjCJrEU9PFP+afPJIkEEhXb9+vdyl3awYaRJ/xXc9GukL\n4IG3bYfXbcd77hhnVoANdOv7OZJVTQNxAaTdDUaaTa3QmJHevOUkn/a9habhdNjgdtqYMdKZAj/m\ncD0M9QTwxx++Fb/3SweYzcl53Q4EfU5qGxgRWADmhXRRgEKaESPdMMDib9h3MW7a3Qe1puFv/vUo\n7DYZ//WhG0wtooGGlO6dt22BLAGzFGSbak3DC2/MI+B1Yh9HxtLvcaCq1FCpsplL4yntBnSTQhb3\n0cxyFtlCFddu5TcfTbC9zgb/w1PHAQC3XNOPO68bhMtpw9eeOY0Tk0mM9gVMb4wO9ej30eRC2tTj\nrgXPkRsCMsvKqrAscGekGRfSBiPN1/dGkiQ8cv8evP/tO5iymCG/C9dsjeHNc3FqxXQiXYLdJnFV\ncpIGDauRgcaMtBi1Ag9YhXQHIehzspN2FyrCyLoJbtjZYzjkskJ/zIflZKEez2EuGoylAIw0A1lq\nraahUKoaGybWILNwrCS4GaI4EOw+AoB73zKCPVuieN9dW/FXj96DrUPmz3HftKcPj/7CfvzSu3aj\nO+zC9FLWdCfRk5MJpLJl3Lavn5thH8Dea4Bcw7xYAI/Lbrge0wSZOSRsEk/s29YFt9OGwW4/fu1n\nr8UNO7sRCbrx0H07kc5VUKmqpsu6AaA74kE44MLpKXo59GRfwVfa3WCkWYBkV/t4zUgz9hrIFipw\n2uVNbQr1/rfvAKBH19FAPFNCNOjm2vRjPTLAM0FCFGzed96BCPicVFid9ZDNVzBQZ5Q2M/q7fDg1\nncRqqmi6tLDBSPN1SgXYbF703E5wY6SdDl1hwSxCTlBpN6DLrv/Xb95J9Rw2WTLm33ojLixNZJDK\nlk11bJ+uy8X3bImadsxWsFbZwULWx/vZ4XXpDDztedasQCNGXWEP/vnj74IsSxdslN9311Z8/9UZ\nzCxljZiEqbMgAAAgAElEQVQ5MyFJEnaORPDSsUXE00Uq0TqGtJvjWhQgTBqj2XvSjOIl7WbtNZAt\nVLjPR/PGDTu6sW04jBePLmBmKYvhXnOcwQGdKEhmSobDPy8EvGwbUo0xo81bTlqMdAch6NXNOMqU\n5YNVRUWponJ3dxQBfTHimGp+AyOV1RfQ8CaRdhO2jpeUDgCCXgcyjBYYEeYORUFfRP8Mpk2ekyZG\ngL1Rvoyln/GIRDpXgSxL/MYkDHUHXVZapPQIALDZ5EvYJoddxu9+8Ca8766tOLDHfDM9YG2ONR1W\nOp0vw26TuLGzAOAzmDRGjLQA65Hfw8ZrANCbUqLcR7wgSRLuv20LNA1448yKqcdO58tQaxrXDGmA\n54y0Je220AEIMIrAMozGNnn3EgD6u0iWdMH0Y2cEknbnGMidyQaJ1+Yf0K9pVhFyxoy0gIw0a/TW\nC+lZswvphF5I84i9WgseMXJBn5NKWsFG4GWUyU7m/ERv6o72B/Gr77uGmqfIznohfYqSvJtcTzwl\nqQ0mjc3zOV8k0m7OhTSDxoGq1pAvKZu+kAaA3pi+p0tky6Yel4yhRDk6dgPsTexKZQU2WeKWmCEC\nNu8770CwisAimxeysG1m9Md0eTuNCKyUQNJuNox05YJz8kDQ50SxrKCq1Kifi8zAi+Y1wAN9UX1z\nYT4jXYDTYUOEsXfCxWBtlJTOV7gaQxE5LCtG2r/J16LtI2FIEnCKFiOdq3BdhwD2BUAj/oofC+/3\nOpEvVVGj4MGyFiTtxVqLGo7aybrDtllI1I8X4+jYDfBhpN1OG3czSJ6wCukOAunK02ek9QLAYqSB\nPoORNr+QbsRf8fuc3U47ZImxtJvjppjlImN8v5a0Gz1hFyQJmFkyb0RC0zQsJvLoi3m5L+JGHjuD\n66qq1JAvVrluir2MHPCzljoKgN64GO4N4OxMynTjy6qiolhWuD+nWBcAhVIVksTXJMnvcUDTgALl\n+yhVZ195NxxFAPkMEiYX0sIw0oxN+4plZVPPRwNWId1RYCXDJXmDVvdSjwNx2mWsJM2XdqdyZTjs\nMtf8PVmW4HU7mBTS5BzEVZIHWI1HkHPYbZIhg93McDpkDHb7cW4uZRr7kslXUCgp6I/xd3RmOSJB\nGp18GWk2DvikqBJd2s0CO0ciKFVUnJxMmHrchtEY38+YvfO9Aq/Lzm08Aljznik3D0jRaKbRY6fC\n63bA7bQhmTFX2p1I88+QBnQfB6/bzqwhVa6om9qxG7AK6Y4CK2OojLV5MSBJErojXiwni6YfO5Mr\nI+R3cWfTfB42hbQxI82RkSbXdIYFI53nP3coEnaMRFAoKZhbMYeVXkrozS0y88YTRpRNkX4klAiF\nj4ehtNthl+HaxBmlBHfvHwIA/PXjR1CqmPe583aAJ2Aff1WFl+OYEbBGzk75PZOi0WKkdUSCbiSy\nlKTdnBlpQL+XWOVIFysK3JvYaAywCumOAqt5VktOdyF6Ih5k8hXD5t8MaJqGVK7C1bGbwOdxMMmR\nzhX5m42x8hkg57AcuxvYUY8FMct5eKHuWyAUI82gQUO8Fbgy0nUVDW1JajZfRcDrsJpRAK7b3o33\n3jmO2eUc/uHJ46YdN00ypDmv9x6XHTZZYmg2VuVqNAasyfylHIGVzFqM9FpEg26kc2WoqnleKfF0\n0Tg2b/i9TuQZxKpVlRrKFZX7fcQbViHdQWDFSIsWOcIbPfX86GUT5d2liopKVeWa20ng9zhQLKum\nLirrQYRCmpW0u6qoKJQUazxiDbabHOFDHLv7BCikjSYng4aUCAwiib8qUn6/mYIV2bMWj9y/B90R\nD77/6oxpx8zUryfea5EkSfB72cRB1WoaimWFa/QVsIaFp/yeDWm3xUgD0D8HTWs0Jc1AIlOCx2Xn\nlku+FgGvvqejbaoqwpiRCLAK6Q4CqxkiI7bHKgIAAD0RUkibJ+9OC8AqERgNGsoyzZzhwMtxRpqR\noQ25h3jLJUXCloEg7DYZp2dSphxvcVVvbPUJIO0mmycWslQRTAoNRpriM0OtacgXq5Yyag2cDhuG\newMolhXT5tNT9etJBHWU3+Nkcg8Vywo0Ddz9KwKspN11szER2FIR0HDuNq+QjqdLwny+jRQJuvsc\nYmIX2uQNGquQ7iAwm5HOW4z0WvREPADMZaRFYJUIiCyH9nUlAiPNStptNaMuhcNuw/hgEJPzaVSq\natvHW0zkIUlAb5R/IU3meDcLI23EX1GUducsZdS6IPE6ZrkOZ4yYPv5rUdDnRKZQMd2Z/GKQtY47\nI80oNi+ZKUGW+KsORAGRuJs1J11VVGTyFSHmo4HGM5N2g0aEpq4IsArpDgIrGVC2UIFNttyGCQxp\nd8LMQlqMuTSAXYMmV6zCaZfhdPAzpmBVSBvFjgDfr0jYMRyBomo4P59u+1iLq3nEQh447GIYnfgZ\nmfaJUUjTd+22RozWB4nXIXE77UKkzXAk6EKtplEfvSEzw7wVYX5G3grJjG5sauPoUC4SokH9ezcr\nSzpRZ7Z5R18REKUDbeWdCH4dIsAqpDsIHhebzN9svoKA5TZsgKa0WwhGmlEhnS9UuTp2A+yk3URK\nZzEAF4LMSZ+aam9OWlVrSGRKhlpEBPg8DsbSbo4z0gxypEkMY4DzM0M0xEL6NW8WIy3SWhQN1CW3\nJjsqX4ykkavMt/BhNa6XzJYso7E1IN97wiRpN4m+ignyGRsmdtQZaXGeHTxhFdIdBEmS9M0aA0ba\nYgEaiATdsNskUxnphbhulNQd5l8I+Dz6ppj2dZUrVuDjmCEN6EyaTZaoMx7nZnXGdaw/SPU8nYZd\nY3ohfaLNLNxUroyaJtbMn9/jQKFUNS0n+3JI58qw2yT4OCqGGow0xUK6aDHS64Fs1s1ipDP5CmRZ\nEsJ5N2wwheZm/F4MwkQSZpIXjPgrimtvoVRFqaJaRmNr0JiRNouRFiNDmoAVIy2S1w9PWIV0h8Hv\ncVJlDtWahlyxas12roFNltAV9pg6Iz25kAEAjA3wL7RYsLS1unEQz/loQG9GBbxO6tLu09NJyLKE\nrYMhqufpNPTHfAgHXDh+PgFNa73gTAompQN0dqmm0WVpAZJPzjd/3mG3wWGXUaRZSFsxjOuCXPNm\nMdLxdBGRgAuyALLfyCZjpAlzmKfIHKYso7FLEK43Fcy8h4CGWoQ3/EYhTZccSVmMNACrkO44+Dx2\nqoY2+WIVmmbJ6S5GT8SLZLZsikkSAEwtZBAJuIR4ALEopItlBTUN3KXdgL4xp/leFbWGc7MpjPYF\n4HZZPgNrIUkS9myJIpEpYakNhYfBAHDeCK8FqxGJdK4sBAPgddtRKFsz0qwRM2ak2x81qlRVrKSK\n6O/iHyEHNIo9swqcy8GIg+LMSBOTQpruyo33Ks6zkjeCPifsNsm0ho1ojDQr126R/BV4wiqkOww+\njwPlCr18OGvzsj7InPRKqv3NS75YxXKyiFFBZL8sDLhEcOwmCPqcyBWr1JxhpxYyqCg17KjPA1u4\nEHu2xAC0J+8WcXPIIku6XFVRLKtCbFw8LjtVabflfL8+Qj7dNCphgrR7KVGApgEDXX4TXln7IEwh\nYVFpgRxfhOeH3+OgyhwS9Y4l7W5AkiSEA27TZqTJmMVmc+1O5cpw2mXDM2OzwiqkOwy0WY9Mztq8\nrAdiatSuSRKwRtYtSCFNHrpUC2kBMqQJAl4HNI2eUyrJSd4+bBXS62H3WBQAcPx864W0KDOOa2EY\nB1HcvIhk7uJ1OagW0uRzFEHFIhJkWUIk6DaFtZ1fyQHApmSk7TZZiMaun7LvDWFdRWgaiIRo0IVU\nttTWiBGBKAoHApYz0qEA3zEjEWAV0h0GY6aGEutBbjyrkL4Qt+4bgMMu42//9Q3MLGXbOtbUol5I\nbxFgPhpofNc0H7oiMdK0peyn682WnaNWIb0exgdDcDltOH4+3vIxEgIxSgSGUyrFTbFIhbTHbddH\nNigpOzJkLRKg+SYaYvVCut3PnpheDghSSId8TkhSY4aZFpLZMiJBMQoAv9dJ1aTQKPIsRvoCdIe9\nUFQNq6n2mzbxdBFBn1OcKEYGjLSmaUhny0KsRbxhFdIdBuqMdN6Sdq+Hsf4g/suDN6BQUvCJL77c\n1qI3Oa8X0qN9YhTSLJysRSqkjcZBns49dHomCbfThuHeAJXjdzrsNhk7RyKYXsy2XHQSRlqUuBEA\n8Nfd7/MU59JEmkkjzt2lCh1WmjyPRFCxiIZoyA1F1dpuBs6v6IW0KIy0zSYj5HeZ5qa8HjRNQypb\nEsZfwe/RFVK0MtmTltnYutgyqO+/JuZSbR8rkSkJI+sGAJfDBqddpkqOlKs1VJSaEH4dvGEV0h0G\nI6qIUqfJmJG2GOlLcM/+Idxz4xDmVnJtzXdOLmQgy5IwhRZxsqb50CWNHxFkmjQZ+KpSw8xSFuOD\nIdgEcMEVFcStnkhLm0U8U4LDLhuNRRHQyISlJ3cWiZH2uvT3S8ulPFeowuPS3cEtXAizIrAWVuuF\ndEyMQhrQmVOajHS2UIWiasY8Nm/QjsAijLQo71cUbB0MAwDOzaXbOk6hVEWxrArXqPB7nVQZabLO\nidDU5Q1rheow+N10GWmSlSzaQ0EUvPXGYQDAc0fmWvp9TdMwuZDBYLcfTocYMiBAb5zQnJEm3Xav\nAFmlRG1BihIzkStWoGliSY5FRG9UN+9birfm3J3MlBAJuoWQZhL4GbjfE0ZaBBaAdpZ0Ol9GwMf/\nfYoIsyKw5ldziAbdQqULRIJuFMsKSpQaNEnRHJY9dGW4y4kCgj4n3E5xvmMRsHVIj6Y8N9teIU2a\nWaJcTwR+r4PqWpStF9IirEW8YRXSHQYfmX2gJAOars//isKWiobrtnUh6HPihTfmW3J9Xk2VUCwr\nGO0T6/Ol7WSdrz90fQIU0oYzLI1Cur4ZskYjroy+OgO2mMg3/bu1moZUtoyoYAxLyEevQUNAjh0U\ngAVoFNLmr0VVRUUiU0J3WIxcVtFgRgRWVREr+oqAzPLSYqUN8y1Bnh8NRtr8oketaVhOFoRSHIiC\nSMCNaNCNc21Ku0kzS5QMaYKA14k8xdn7XEGPghVBHcUbViHdYfAbzrB0Ok3Ti1n0RL2b3s7+crDZ\nZNy2bwCpbBlvnltt+veXEmLNpBEQJ2taSgey2fa4+V9XNAtp0gEWYRZcZPQRRrqFLOlMvgK1pgnH\n+pMNBU1lB7lmRWABPBQZ6ZVkEZoG9MW8ph/7JwGxoL5pbycCazFOoq/EWotoO3eTyCNRnh/Gno7C\n2ruaKkJRNaNxaeFCbB0KIZ4utZUnbTDSAs1IA/Rn77OGtJv/WsQbLRXS1WoVjz76KB5++GF84AMf\nwMzMzCU/s3fvXnzwgx80/lNVte0Xa6HB6NEoeNK5MlK5MkYsNvqKuPP6AQDAC6/PN/27pHAg0lZR\n0IjAosMCkM22CIx0pG4ykzIpQ3ItyGYoIMAsuMjoaUPaTTY9IhmNAbq0W5LoMtIiZSuTZmuBggR3\nMU6ek1YBsB5iYf3aX0q2NhoBrJmPFqyQpp0lnRKNkaYYm7dY/477usTab4iCbUP6nPREG3PSKyn9\nHhRNPdNIJ6FTSJMZaWv2HmiJHnryyScRDAbxqU99Cs8//zw+9alP4S//8i8v+Bm/348vf/nLprxI\nCw0Qs7E8BRaAyLpFkx2Lhr1bYvC4bDjaEiMtZiFN28k6b8xI82ekSQeVjrTbchreCNxOOyIBV0vS\nbsIAiMIoEdhk3bSPzDHTQCpXhtMuC6EYMszGKDAeRLljMdLroy/mg02WMLvcmlkfoM9HA8BAt9+s\nl2UKSKOzHZbwShCOkfbSi80jz1dL2r0+tg425qRv3NXb0jFWkvp4RXdErELavyZLuh/mf//WjHQD\nLTHSL774Iu677z4AwG233YZDhw6Z+qIsXB7koUuDkSb5yCNWIX1F2Gwydo1GMbuca5p9IoV0j6iF\nNKWRAZHMxhx2GX6Pg8oMHun+WtLuq6M36sVysghVrTX1ew2zIPEW8JDfSU3VAehsdyggRv4tTbMx\nURuOosBukzHQ7cPsUhaa1toM5MySXkgPClZI05Z2N2akBSmkKY7rEdWBJe1eH1vrjPSxiXjLxzAK\naUEZaVomdpZrdwMtFdKrq6uIRqP6AWQZkiShUrnwIVCpVPDoo4/ioYcewhe/+MX2X6kFAGsiVig8\ndKcX64V0rxj5xiJj73gMAHD8fHMP4KVEAZIEdIfF2iDSlnbnSwqcdlmYKJtI0GVI/MyEZTa2cfTF\nfKjVNKw2OeeZyIrJSANA0OdCtlBtujmwEWiahnSuYpia8QYppGnEXxFpt1UAXB5DPQHkS0rLDcGZ\npSxkWcJgt1ifcYSytDtZZ6RFkaT6KM5IN+4jsfYboiAWcmPXaASHTi3j5FRrkaYrqQL8HocQJMFa\nBNYw0jSQL+njuiKMGfHGVfVhjz/+OB5//PEL/u7111+/4M/rdUQ/+tGP4r3vfS8kScIHPvAB3HTT\nTbj22msve56ZmRlUq/Qyz8zGxMQEl/NqmgabLCGRypn+Gk5NLkMCoBRWMTHRek7yZkDErS/GBw9P\noNe38UJgbjmDkM+BmelJKq+r1WuikM0AACZnFjHRZb6fQSZbgMshc7tvLobLriFbqOLMmXOw2cxj\n9+YWdbl/KrGEiYmMacf9ScDF371T1u+hw2+exY6hjbNiU7PLAIBCZhUTE81Lw2nCLulr2NETZxA0\neU6+XFFRqapwyKoQ91GmzsRMzi5jYsLc9zq9kITDJiG5MofUKn32XYTPs1kEnHoD4+Ujp5u6fwAS\nw5hCd8iJmekpGi+vZZCxtcWVFJXvJZ7Kwe2Uqa3BzYIwewvLyXXfbzufwdR8Ag67hNTqPNJx/ioW\nEfGO/RGcnEribx5/Db/1s+NNqX00TcNSvIDukFO4Z0g+q7uRT84sYDhsfjGdLypwOWThnh80MT4+\nvu7fX7WQfv/734/3v//9F/zd7/3e72FlZQW7du1CtVqFpmlwOi/sSjz88MPG/99yyy04ffr0FQvp\n4eHhq70UYTAxMXHZD5QFAt4zUDTZ9Newkj6F3pgXu3ZuM/W4P4kYHFbxuW9NYjahbvh7qCo1pPNH\nsWdLjMr10851WZLiAKbgcAeovLaKehpBv4vrfbMW/d0JnJ3LI9ozYGpshXwwCQDYtX1cuJkpnljv\n2ty9asPTr65AdoUwPj66oeNomobJfzkPh13Gjft2CMcCDPRm8fq5DCKxfoz2m6vsWYznARxHf09E\niPuot78KfO0siord9NeTzJ1EX5cPW7duNfW464H3et4qrk068PRrK1Blf9OvP54uolh+E9fviAr3\n3ms1DZJ0AjXJQeW1qdo5+DxOYd53raZBlk+iWrv0Pmrn2tQ0DYncCfR3+ZncR52K8XHgpdMFvHRs\nEVk1gOt39Gz4d7OFCirKmxjsDQtzPRGkq8sAZuD2Bqm8tlzpJEIC7el4oiWd5e23347vfOc7AIAf\n/OAHuPnmmy/494mJCTz66KPQNA2KouDQoUPYvn17+6/WAgBdCpQx2RQqnSsjnatYsu4NwuWwYftw\nBBNz6Q1LG1dSetyIiHN/DYdHSjPSxSo8AhU9Rlapyc7dJAvUcu2+OnpJlnR846zyxFwaM0s5HNjT\nK1wRDQAhn35dpSmMSBA/BlHiRnweBwJepyEfNQu5YhW5YtVy7L4KhurpGjMtGI6J7IciyxL8Hge1\ntahYVoQw6yOQZQlhv8t0KXsmX0GhpFhGYxvAvW8ZAdC8ezeZj+4RsGlO27W7UFIsWXcdLRXS73rX\nu1Cr1fDwww/jK1/5Ch599FEAwOc//3kcPnwY4+Pj6OvrwwMPPICHH34Yd999N/bt22fqC9/M6Aq7\nkS1UUKqYN5tGHgjWLM3GsWdLFLWahpOTG5PBk6ifPgELafJApJGBW1VqqCg1+ARw7CaglSWdK1Rh\nt8lwOW2mHvcnEb0tZEn/8NAsAOCe/UNUXlO7IMYrNJy7yTHDApm79MW8WE4WUKu1Zni1HpbqjRUR\nn5MiYahuEkaK4mbQ8EMRr5AGdFNVGj4wgHiFNKB7dpjtUm4Y9ll7uquiq24UFm/Sr2O5Hj8novrM\nT3FGulxVUVE0ywumjpaeJjabDZ/85Ccv+fsPf/jDxv//zu/8TuuvysIV0RPRH4wrySKGTVoICYMS\nFGiTJjp2juqGe2dnU7hh59XlQKI6dgO6c6gk0SmkRXLsJiCRDWYbjmULFfi9DiFclUVHLOSB3SZt\nOEtarWl49vAcfB4HbtrdWlQJbRBGOkMhWo0w0kGfGIw0oDdDzsykkMyWTBuRsAqAjcHtsqMn4sHs\ncguFtMFIi6lAC3gdWE0VoWmaqc9SRa2hqtTEK6QDbpybTaNQqpq2Tho54RYjfVXEQrpx5Wq62NTv\nNRy7xXtW0XTtztb3iSKtRTwhhoWuhaZAmBzSDTMDpIAKWTfGhrGtHp1wZia1oZ8XOdLFZpPhc9OR\n05F4HJ9AhTRxfDY7AitXrFqy7g3CJkvojng3zEi/eXYViUwJd1w3AIddTMafNCJTFBhpop4QxW0Y\naLhqmynvbjwnrQLgahjqDSCRKTcdhzm9KKZjN4Hf60RVqaFcNdf4koxheQVSRwF0nMonF3Szy6Ee\nseLNRETI54LdJjXNSK+kxMyQBvRrXJYlKns6Ui9YxJsOq5DuQHRHSCHdXPfsSiCyQSsTbuPoCrsR\n9rtwdvbqhbSmaYYET9QNYsDnpMJI5w1GWpzNS4ORNm/jUqtpyBUq8Huse2ij6It6kcqVN+Qz8PRL\nujvo224S15iSzC/TmJE2Ni8CzaWRUaBm5tyvBrI5FXHuUDQM9+iKtIn5jc92krWoP+YTtiEV8NBh\n04r1pq5ojDRpjpnZ2D0zoxtfbhuOmHbMn1TIsoRo0I14qllGWlxptyTpXgPEt8VMEEbaknbrsArp\nDoTBSDcxW3g1kPxgS6qxcUiShG3DYawki4bscj0sJQr4jT//AV46tgiPy45oSLz8WwAIep3I5ivr\nxtm1A7J5EUnaHQmaX0gXywpqWmM2ycLVQRjNq7HS6VwZB48uYLg3gN1jURYvrSWQjOcMTUZaELMx\noLEWmclIpwVk3kXF/vpI0bOH5zb8O8lsGbliVUijMYKAj858J2nYiVZIRwJEIWXOqFGtpuHsTAqD\n3T74PdZ6tBHEQh4ksmWoTfg9rKSKsNsk4/sTDbppn/nSbhGbujxhFdIdCNL9MlPabTHSrYHIu6/E\nSn/nxUnMLGVx67X9+F+/eQdsspjzsyG/C2pNa1omeDUQRtrnEWfzQphDMxmAXP1zs7q0G4dhOHYV\nRvP7r85AUWv4qVtGhZ4/D9Q3FlRcu7Pi+Vg0GiHmMdKkCWFt0q6O63Z0oyvkxrOHZzdsPkokv0IX\n0pTmO4UtpIPmpkjMr+aQLynYbrHRG0Ys5Eatpl2RFLkYK8kCYiEPZEH3dIG6aZ/Z5Eim3uAKWnsd\nAFYh3ZGIBd2wyZLFSAuAbUMhAMDZK8xJn57WJVa//eAN2DIQYvK6WoGxmJs8N0zMxjwucTrjdpuM\ngNeBVM48szHCnliM9MZhzNgmClDV2mWbOP/x8jTsNhlvvVFcWTegX1d+j4OOa3e+ArfTBrdTnCKg\nK6xvIk1lpPNleFx2YWXHIsEmS3j7gREUSgpePLqwod+ZnNcLaZHXIvIMzZjMSBdIIS3QmBFgPiNN\nfFu2D4dNOd5mADFLXN2gvLtQqiKZLQsp6ybwex1QVA3lirleAxYjfSGsQroDYbPJ6Ap7TJ+RJvmN\nFjaObcNXNhyr1TScmUlhqMcPn+CfbWNOy1wn63yxbjYmECMNAOGA21RpN4lrsRjpjWNtBNaX/v0E\nPvTxpy+JvakqKmaWstizJdoRC3fI7zQak2YinSsjKJCsG9AbB91hj7mMdL5iKaOawNsP6Bm433lx\nckPM0/kFfZ56S7+Yjt3AWkbaZGm3oDPSZo8akf3IjhGLkd4ousJ6M2OjhmNHTq9A04C94zGaL6st\n0MqSJutboAPWYxawCukORU/Ei0SmhKpiTqcpky8j6HUKK1ERFbGQB9Hg5Q3H5lZyKJaVjljQosTJ\n2iR5GUGhLF78FaA7pWYLVVSVminHI9Juqxm1caw1qzr4xjwKJQWzK7kLfoZsbGKCegtcjKDPhWy+\nYmq2MqBfX0EB1Q69US8SmbIpDsuapiGdq3REw0QU9Hf5cNPuXhw/n8C/v3D+qj8/OZ+By2kz1CAi\nglYBUCRrkWiFdJ2RTmTMaWKfnk7CJkvYMiiu6kA0xIIkS3pjBNUrx5cAAG/Z00ftNbULouww23As\nm9fvI+s5rcMqpDsUPVH9pl9p0mXwckjnKkLN3nUSxvpDiKdLhoR5LYise0cHSKwiFJxDAaBAGGnB\n5HSNxoE5mxey6fNbjPSG4fc64fM4cHIyYRiOXTyy0iikxZXQrUXI70RNM9coSVFrKFdU4ZpRQEOe\nb8aoUbGsQFFr1ohRk/jN91+HoM+JL3zzGM5fwcG7qtQwu5zFWF9Q6Ka5UQDQknYLNGYE6Ay522kz\nZe1V1BrOz6Ux2heEy2GNR2wUsSYY6VpNw6snlxD2uwyfHBHRaEiZex9ZjPSFsArpDkVvxDznblWt\n6WyHdVO0hIEufSM5v3KpvPFUvZDe3gGMtDGnZVJhSdCIvxJr80IYztUNdqCvhoa0W6z3KTp6o94L\nmKeLHbwTHcZIEyM7M6PkCiUx82+BRgOuGZOey8GavWsNsZAHv/3QDVDUGh773unL/tzschaKqmFs\nQFxZN0CTkRZT2g3o62/KhLGqZKaMilLDcK+4ZnIiwpiR3sB+4OxsCqlsGTft7u2IhpTZ91G2UIHT\nLlmNmjqsQrpDYWaWNDH0CFksQEvo764X0qu5S/7tzHQSdpuMLYJvXAB6M9KiFgFd4bqUK2XO+yUO\ns5a0uzkQeTfBxc+0eKazCmny/ZvpOFwQtBkFNBQYZrAepBgPCTYL3gk4sLsXPVEvDp9ahqKuP65C\nHG8CipMAACAASURBVLtFno8G6DFpos5IA/r6m8pVmopfWg9ExksixCxsDEShltgAI01k3Qf29FJ9\nTe3C76HjNZDJV4RTGPKEVUh3KMzMkjbiRixpd0sY6PIDAOZXL2SkK1UV5+czGB8MdoQDbZiWtJvE\nXwlWBJBC2qzxiKxlNtYSeqN6I4oszJdKu/Xvh2x0RAcxFTRzLo24mYtoWBisb9gz+fYbB+k8aepa\n91CzkCQJB3b3olBScOJ8ArWadon52Pm6Y/eYwI7dQOM6p5UjLVpTF9ANx2o1Ddk2lSzWOtQaHHYZ\nYb/rEtfu+dUcDp1cvuDvXjmxCLtNwvU7ulm+xKYRoMhI+9zi72lZwSqkOxSkCDBDlkoyTy1GujUM\nEEb6IpOks7MpqDWtI4zGAMDttMPrtpvqZA3ojLQsS3A5xXrwdoWaMxe5GkgDwpqRbg6Ekb5uRzcC\nXucVpN2dMSNNvv+ciXnsBYELAL+JDstWhnR7IAzZwaPz+O+fewG//9kXAOjO9z98bQYvH1sEAIwJ\nzkjbZAk+j2PT5EgDQNSkCKyGV4d4TTfREQ25Ec+UjAbU1EIGH/k/z+L/+cKLxvcSTxdxbjaNa8a7\nhFQIrQUN9/tKVUWxrAqXwsIT1ifRoSDsoRlFjzWX1h56I17YZOkSRvrE+QQAYM+YuPEIFyMScJsf\nf1WqwuuyQ5LEmiUi5iJmNKOqSg3HJuLoj/ms+6hJ7B6LQpaAO64bxHKigOnFLDRNM66XeKYEWWrM\n4oqOgJeCtLsopqoDAIImynCJiY0l7W4N127tgstpw5PPN9y7S2UFT75wHl966jgA/X4TUdlwMQJe\nBzVGWrQcaQAI1yOwkpkytgy0fhwrhrF19Ea9mJhLYyVZhCRJ+IO/PWg0Jk5PJXHzNf149URnyLqB\nta7d5q1F5J60GOkGLEa6Q+F22uB02JAyweAlXWcBrOzO1mCzyeiNei8xGzsxqRfSu7dEebyslhAJ\nupDJVy47Y9cKCsUqvAJu3EI+F+w2yZQZ6ZOTCRTLCm7c1WPCK9tc2DIQwmN/ej/uvH4Q3REvKkrt\ngudaIl1COOCCzdYZy5UxI23i5iUvqM8AYK6hTdoaM2oLTocN12+/UG46t5LDuXo848d/7TZ88jfu\n4PHSmobf69xUZmPhevOo3T0d+cysQrp5XFe/d149uYRvv3geqWzZKJiJcWxjPlrc2CsCGl4DhHiz\nZqQb6IydiYVLIEmSbk5hBiOds6Td7WKg249soWJ0gzVNw8mpBLojHkOG3wmIBNzQNHMceAkKZUXI\nh64sS4iGPKYw0q+d1BfXG3eL36UWEW6nfn1c7P2gaRri6WLHzEcDawxeTJyRFtlszMzNmqWOah/v\nun0Ltg2H8c7bxgAAs8s5TC9l4XXbsW9bF2wCuwyvRcDjQKWqmpJPTlAsK3DYZdgFbMqRyDeiymgV\nZA9iSbubx4H6+v3ysUU8e3gOHpcNv/HAdQD0KNNyVcWRMysY6vGjv0vcHHYCGsaXjULaYqQJxHua\nWNgwIn4X0rnyJYYizYIYvFgsQOsgD9X51TzSuTIWVvNI5yrYPdo5bDSwJks6Y04hXatpKJYVIQsA\nAOgKuZHMlKC2ycC/dnIZDruMa7Z2joxfRPQYsX56cyNXrKKi1DpmPhpYm4FrJiMtrrTbb6IxlOXX\n0T727+zB//6vd+OWa/oBAFOLGcyv5DDcGxBuvOZKIBm1Zs53FsuKkGw00FAEElVGq7AY6dbRE/Vi\nrD+IQ6eWsZQo4Oa9/YiFPBjs9uPMTAqHTi6jXFE7go0GdLWk1203lZG2pN2XQswnioUNIRxwQVE1\n5IrVth6aFgvQPkiW9Ke/dgSTCxnsGtUNxjpJ1g2YH4FVKCvQNDElqYBuOFbTgESmjO5Ia8VaPF3E\n5EIG+3f2GMyqhdZAGOkjZ1bww0OzuP06fVgw2iHRV0CjsMybKO0msT1eAQ1ebDYZPo+jbbdhQDcb\ns9skYZ8XnYShHj1N4pXjS1BUDSMdlivcMEqqmtZIK5RELqTNyWMnhY4Vw9gaDuzpNWLi7rxhEACw\nczSC7786g7/7xlEAwD37h7i9vmZh9ogEqRf8Aq5FvGAx0h0MswzHyIM7aLEALYNEYJEH8MkpfZ5m\n91hnFdIRwznUHEaaXFthQc2DjCzpNuTdxybiACB8FEYngDQznn5pCi8fX8QX6huXTsmQBnT5tSRR\nmpEWtAjQjaHMiL8qI+hzdhRzKiq6Qh44HTZjTRrp66xCmig7MpuFkfaZw0gTJYxVSLeGA7t1ttnn\nceCGHbrnCUleWUkWceu1/RgfFDs+bi38Hoepqg7SMPVajLQBq5DuYPz/7d1pdFzlmSfwf+17SVWS\nSrtly2BsQN5iE5Y4OAtLCGF6SEyHbtMnJIROEzg9fQyEADM582GSkCaZ9IRkCIlZhsNpug2dtKeT\nk3RnwAlNswQEjjEOxha2dqlKpVLt+50PVbe01XJvVUl1r/z/ncM5dpVkv8JvVd3nPs/7PIXmFDUE\nPYIgYHo2CrvFAIOe26Fa4t3/ZocJD935EXS32eF2mhQ/ZmQpl7O+GenZYO7PaVZox+V6dO7258vg\nxTFOVD2xtBsAjHptIThrUdEZaa1WA6u5vhcvUQXPkQZy2cNQNFnzMaNgJMkbunWi1WrQ02Yv/H5d\nu7o+i8QKuWCNgaVIEATEFRxI2ywG6LSawvGGauVm/OpV05xRaTb1ubBrSztu+sT5hWviCxaMML35\n6gsatbSqOKwGxJMZpNL1aSBbyEizaqiA/ydUrB4Z6eHJECZnorh8a2e9lnVO8rituHf/LvT3NKG7\nzY7/dWAvkqmM6j7MxKZOgTqdkRY7kIqZbqURZ0n7aujczYqO+rFZDBjY2AqnzYjLBjrx8DNvAgDc\nKjojDeSzAHXNSCu32RiQC6RT6SwSqUzVxxtS6Qyi8TSnR9RRj8eOofE5AECvykq7XXWaqyxKJDPI\nCsocfQXkGsg6bcaabxyEo0nYeD66ajqtBt+47dJFj63vcqKr1YaL+luwoUs92WggV9oN5Jpf1uM6\nTKwQYUZ6njLfUUiSwnnWcPUfNP9+dBwA8JGt3XVZ07lMPE8D5MaQGA3qe6MRqxzqVdotNi1Taka6\nHqXdhfJ1hf6MavPNO64AAKQzWTz5L8fhm4urqrQbyJWljk6H6/bnReNpaLUamI3KfE8pdO6OpKoO\npOd7dfB1VC/d+Uopq1mP1mZ1vYYKjS/r9Fkkjr5S6vEIIHdOeno2WtOfEYqlChVyVB96nRaP3veJ\nRi+jKgt7DdQlkGZGehl1pctokXqUdr/8h3EY9VrsUsFweVp5YqfUenV5FLMJLoUGmWKA5g3UEkjn\n57CzWV9d6XVa3P6fB/DRHd2LSlTVwG4xIFHHcrpIPAWrSa/Ys8MOsVN5DSO/+DqqPzGgUlvHbgBw\n5aujxONBtVLyDGlRk92IaDyNVLq6kV/JVAaJZAYOC19D9abRaFT3GgLm35vrdU0XjCRh1GthNDB8\nFCn3HYUqqrW0e3gyiJGpEC4b6FT0hwutHr1OC7NRV7eyVHFvuhR6xrXZYYZWA/jnaijtjiSg02oU\ne35VzS4b6MJlA12NXoZsC2dJ1yMLEI2nFd3JWrwBF6yhc/c7Qz4AQK/KmmIpWV++R4faylGB+mek\no2IgreDXUVNhlnSyqk7l4uc2Z0iTqPBZVKfO3aFIkhN+luAtBRVrzl+gBaocl/D7d6cAAJcP8Hw0\nzavn+U7xIkipXbt1Wg2aHaaazuHNhRNosrPTMM2r9yzpaDyl2PPRQH1+3tfemQQAfPgidcxoVYO+\nDif+6xc/jD+7Rl0NkoBc5tho0CFQpzPSashIO2ucJS1mHTlDmkQrkZF2MJBehIG0itnMeuh12qoz\n0lP+3FkcNd6tppVjtxoRqdObbiCcgFGvVXQ2zeU0wx9MVN1xeC7MTsO0WD1nSWezAmKJtKIrHpz5\nC/dqRxUFI0m8MzSDC9a56jYzmHIuuahDsc0ey9FoNHA5TOfcGWmg+lnShdFXzEhTnr0QSNf+WZRK\nZxFLpJmRXoKBtIppNLlsWrUZ6Zl8OavaGvnQyrJZDIjE08hkaxtlAwCBYBzNDpOis7UuhxnJVK5j\nsFzJVAaxRFqxGXdqDDHorUdlRyyRhiBA0TejCp1hqwykXz8+iWxWwKWsjqIFXA4TAqEEsnX4LIrF\nlZ+RLsySrvKIBDPStJT4WRSN1/5ZJO4vJg4WYyCtcs35D5pqsmkzwRiMBp2iMx20+ux1euMVBAGB\ncELx2ZD5s3jySwjFEjwnR/bQArUGlguJo69sCi7tdtZ4RvrVdyYAAJcxkKYFXE4zMlmhLmWp6ijt\nzp+RrjEj7WBGmvLEz416VEeFIuKNGu6vhaoOpF9//XVcdtllePHFF4s+f/jwYXz2s5/Fvn37cOjQ\noaoXSOU1201IpbNVZdNmArmxMkrOFtLqq9f5znAshXRGUPxYKHehO6z8i5e5iLLPgFNj2OuZkY4r\nv0nSwhEr1Xj3gxl0ttjQrbLu7LSyam2oulD0HMhIi13z7cxIU149q6M4orC4qgLp4eFhPPHEE9i5\nc2fR56PRKH74wx/iySefxNNPP42nnnoKgUCgpoVScWI2TW55dyqdRSCcQCvPo9ESCzsO10IcW6L0\nQFrsKO6vYsyKeJaNGWlaqJ6BtBoy0rU0tAlHkwhFU4WZx0QisZqplmaQIjUEmbWekQ4VMtLK/Rlp\nddWzX4cYSDtsyv0saoSqAum2tjY88sgjcDiKj6k4evQoBgYG4HA4YDabsXPnTgwODta0UCqu2ju2\nYpDD89G0VL0y0mKTGKWXdrudtZd2MyNNC9Wza7eYSVPyGWmr2QCtprpAemImAgDoarXVe1mkcvUc\ngSUGmUpulFTrEQnx9cdmYySyiKXddTgjHeQZ6aKq+mS2WMpnMX0+H9xud+H3brcbXq+3mr+KKph/\n45X3QcNGY1RKvbJp8zOklf2mW8h6VFHaLb7u+MFCC9WrqgOYzyQouZeFVquBzWKsKgCY9OWmR3S0\nMJCmxQqBdBXvzUuJ5zuVHGQ6rEZoNbV37WZGmkQ6rQZWs75OGen89Y7VCKA+k13WgoqB9KFDh5ad\ncb7rrruwZ88eyX+JlEZYIyMjSKXqM3NzNQwNDTV6CQCAeGQOADB0dhztNukZtXdP5b5PSEUU87NQ\n7erxbxkNzQIAzgyPo9tZ/QXMqTM+AEAiElD0HgsFcx8Iw+M+2es8MzoNAIgEfRgaitV9bWuJkvdA\nvUXyWeRp31zNP/fZ0RkAQDg4i6Gh2rsXrxSnRYtpfxSnT5+W1Xfj+Pu51xBSwYbtkXNpb6pJNJS7\nyXJmdApDQ7X1xp2eyV3z+CbHMOtVbl8Yq1kH3+z8dZmcvTnly/2M3slRBHzsJUw5Jr0Gc6FYze9z\no+O5hGgo4EWzx3LOvW/29/cXfbxiIL1v3z7s27dP1l/m8Xjg8/kKv5+ensb27dvLfk9vb6+sv6OR\nhoaGSv4PXW0z8UkAozBZm2St6Q8jpwEAmzb2oL+/a4VWR6upXvvSn5gCMAqzTd6eWup37+YCy83n\n9aF/g7vCVzdOTyoD4D2kBL3sn1f7+9yFy4WbNqCLjZJKUtJ75mrIjY47gazGUPPP/daZDIBxrF/X\nhf7+jrqsbyX0dnoxNjOJFk+PrL4Iiddzr6EdF29Ej6f4cbGVdK7tTTWxN0cBnIagM9f8b5QWzsJq\n1uP88zfWZ3ErxOU8g0Aojv7+ftl7M5IYgsNqwAWbzlvBFZLaNDnOYno2WvNrSPNqLsmyZdMGhAOT\nfN/MW5FbVtu2bcOxY8cQDAYRiUQwODiIXbt2rcRfdc5zVHmmZmYuF+S0srSbliiUdtfpjLTSm40Z\nDTrYLQb4qygfDBSajSn7Z6TVpdNqYLcYqi7RXEgNzcaA+dLsKX9E1vdNzESg1QDtbutKLItUrNAD\npk6l3UpuNCZyO00IRVOFcV1SZbICpvwxHpGgZWwWA6LxdP4Gb/UKzewU3GegEaoKpI8cOYJbbrkF\nL730Er73ve/hi1/8IgDgsccew1tvvQWz2YwDBw7gS1/6Em699VZ89atfLdmYjGrjzH8whGQG0v7C\nGWl27abF6jUuQQwylR5IA7nO3bNVdO0OhpPQ6zSwKbgRFDVGd5sdE74IUulsTX+OeLZNyc3GgPlA\neHImKuv7JmciaG22wKDXrcSySMWMBh1sFkNdunaHYik4FXw+WtTX4QQAnJ0Myvq+mbkY0pksOhlI\n0xJiciRWY8OxYCQBg14Ls5Hv1QtV9cm8d+9e7N27d9njt99+e+HX1157La699tqqF0bSiM3G5HZL\nnQnGodXMN/MgEhU6DtfYKCkUSarmTdflMGFkKoRUOiPrgj4QTsBpM3EWOy2zrsOB94ZnMe4LFy6O\nqyE2hhTnnSuVGEhP+aUH0olUBjNzcWw9r3WllkUq53KYqqoWWiiZyiCRzKgiI72hK/de8cF4EBe0\nS/++yXz3+w52v6clFiZHankNhCIpOKxGXu8swW4EKieOHZFb2u0LxNDsMEGn4xagxQodh2ss7Q7H\nUrBbDKp40xWDFLndYYORBJo4Q5qKWJcPnocnQzX9Od7ZGExGnaLH9gALS7ulB9LixX8nL/6pBLfT\njFA0iVQ6U/WfISYanCoIpNd3NQEAPhifk/V9E/nu950tPCJBi9VrlnQwklD851AjMIpSOa1WA7tV\n3tgRQRDgD8ZZ1k1FGfRamIy6mku7w1F1nEkDcqXdAOCXUUIYCCUQS2QUnymkxljXkTvOVGsgPT0b\nhcdlUfwNKU+htFv6GelJXz6QZjkqleDO93GpJSstnu1U8ugr0bp2B7RaDc6MyyvtLmSk+VqiJcSM\ndC2zpFPpLCLxNAPpIhhIrwEOq1FWaXcwkkQqneUMaSrJbjHUFEhnswIisRQcKrhwAXINXgDIOif9\n5h+nAIBlqVRUnxhIT8m7IF4oGk8hHEuhzaX8LJPJoIPbaZKVkZ7In6dmOSqV0pK/USk2SK2GeH2k\nhiZJRoMO3W12nJmYQ1bC6FjRBKs7qARbHTLSgXzzWJeDccNSDKTXAKfNiHA0iazEjnze2XzH7mZm\npKk4u8WAiMxz9wtFE2lkhfkycaXz5AOV4Snp2cPfn8gF0ru2yDjIRucMt9MMm1lfU0Z6Ov9e3a6C\nQBoA2t02eAMxZDLSGqx5Z6P571PHz0erbz4jXX3DMbEZqxpKu4HcOelYIgN/UHrgMzkTgVGvZaBD\ny4gTH2oJpMWGfy4n+yotxUB6DXDajMgKueyFFCPTuQu7RszsJHWwW42I1DAuIZwPwtVQSgcAF29s\nhUYDvH3SK+nr05ks3npvGh63Fb3tfB3RchqNBus6nBj3Rao+3zmdDzTbXOq46dneYkU2K8AbkJY9\nFI8kNdl4cUbFiUfQxKZ71QgVPo/UEkjnzkmPzUh7HQmCgElfBO0tNmi1yj4CQqtvvtmYvJFqC81n\npPlevRQD6TXAYZU3S3p0OgwA6PHYV2xNpG5icwqpN2eWCqvoTBqQuxl1Xk8z/njGL+lnPvGBH9F4\nGru3tCv+7Co1zroOB7JZofCeK5c3XybtUU1GOt+5W+IIrGCh5FYd7xO0+sQjaLUF0rn3dLWc7xQ7\nd4/7pP3MoWgKkXiavQaoqHo0G5sNieNMWfGwFAPpNUA89xOUWIo7ms9IM5NGpRTuYFbZubtwJk0l\nGQAA2L6pDemMgHeGZip+Lcu6SYpaG46Jpd1qCaQ7xIZjEs9JiyPyTAblj8ijxhCbOfprCaQj6qqQ\nWt+ZD6RnpP3M86Ov1PE+QaurHs3GAvnS7mZmpJdhIL0GFGZJS8xIj0yFYTXrWaJBJYkBcLWzpMVG\nZeKdUDXYcYEHgLTy7qGxAADg4v6WFV0TqVtv/vjMmLe6jLRY2u1xq6W0WxyBJa1zdyia5FxSKksM\npGeCtTcbU8sZabfTDKtZj+lZaZ3KC4G0mxlpWq4ezcZmWdpdEgPpNUAMeqR07s5kspjwhdHrcfDi\nhUoS79xXm5EOq+xMGgBs7nPDbNThrfemK36tPxiHw2qA2aRfhZWRWokNHattlDQ9G4Vep54GQl35\njsHjXomBdCSpmnJbagy9Totmu6m2jLSKunYDuf4K3W12eOeSkhr3iRUv3TyuR0XUJ5DONxtTyWfR\namIgvQY48+fLpJyRnvRHkc4IfMOlsuw1lnarMSNt0Gtx4YYWjE6HCzcCSvHPxTk/mioqzCevOpCO\noa3ZopoGQm6nGWajTlIGPpPJzSVV0/EPagx3kxkzwTgEGeOgFgpFU9BoAKtZPZ9HPR47MlkBU7OV\nj0mcHpsDAGzsblrpZZEKWU16aDSoaaTpbDABrVajmptRq4mB9BrgzHc8lRJIj07xfDRVJmbSpiV8\niBcjNndRyxxpkdgsqVxjm3gijUg8zUCaKrKZ9TAadLLmk4uSqQwCoYRqOnYDuUxaV5sd475IxXGM\nhfcINhqjClqazEgkM4jEq+s6HIomYbcYoFPJDSlgfqrKWIVGhYIg4NRoAG0uC5rsLLul5bRaDawm\nfW1zpMMJNNmMqnoNrRYG0muAGKyEJGQPR9ixmyQQu39OzEgr0VxKjaXdwPzM0pkygY8/X+Ikfi1R\nKRqNBm6nqaqMtDhCSm0zlrvb7EimMhW7LKuxISE1xnzDserOSYejSdV9FolVg5U6/vuDcQRCCWaj\nqSybxVBzszGWdRfHQHoNcMhoNsaO3SRFe0vu4n3CV2UgrcLSbgBokXDBJp7VY0aapHA7zQiEErJn\nsvvyHbvbmtWTkQaArjbxnHT5AECsoOIZaaqkllnSgiAgGEmpptGYqEdiIH16NFfWfV5P84qvidTL\nZjFUfVQvlkgjlsig2cmKh2IYSK8BcuZIn50MQa/TqC7LQavLbNTD7TQXuoHKVZgjrbJAWlJGOv9c\nCwNpksDlNCMrAHNhaR14ReL7eZPKuqR2t+UCgDFf+QCAGWmSqpZZ0vFkBulMVjWjr0RdrTZoNJU7\n/p8ezU2Q2MhAmsqwWQyIJdKSmtctFWDH7rIYSK8Bep0WNrO+Ytdu72wMp0YCuKDPDb2O//RUXmer\nDb5ADKm0/DfeUDQJq1kPncr2mZTMhxhIs7SbpHBX2XAsGMldvKgtY1sIpCsEAGEG0iRRta8hYP4G\nltpeRwa9Di0OY6GKsBQ2GiMpbPlGewGZN3QBduyuRF1XuVSS02bClD+CP57xl/ya3701CgDYu7Nn\ntZZFKtbRYkVWqK7hWDiWUt2ZNGDhWbzSF2wzLO0mGaoPpNVZ+ix1BFYwkqtaUdvPR6tvPiMt/4y0\neDypo0V9M5Y9LhPmwsmySZJTowG4nebChACiYi7e2AIAeOGNEdnfK2akm5mRLoqB9Bpx/Z4NiCcz\n+NojL5V8ofz2rVHodRpcsa1rlVdHatSZvyCu5px0ON8lVW0cVgMMem3ZoKeQkXaq6+wqNYY7f65M\nbufu+UBaXRcvdqsRTpuxYkaapd0klXgBPxeufHxtKfGsfleb+hqseppzP3epzt3BSBIzc3H0MxtN\nFVx1SR8sJj3+5d+HZFcZzrK0uywG0mvEDXs24n/81RUwGXV48l+OI5HKLHr+7GQQH4wH8aHN7bxw\nIUkKnbtlBtKpdBbxZEZ1o68AscuyWVJpt4uNN0gCKVUOxag1Iw3kyrun/FGky5zHCxU6+6vvfYJW\nl9gobC4ivyx1LP/51aPCQLqnLffe8dZ700Wfn/bnqsXEKhCiUmwWA67+cB/8wQReentM1veytLs8\nBtJryMDGVlz/kX7MhhL41StnFj336rEJAMCVO1jWTdKIpXByG46FY/kLZIv6AgBA7LIcL9ll2T8X\nR7PdxD4DJIlYcukPVddsTI03PrvabMhmBUz5Sx8LUfONAlpdOp0WDquhqoz0WCEjrb5gc+sGJywm\nHf7t98NFP4+8gdzrS02z5qlxbtjTDwB4UWZ5N0u7y+OV4BrzJ1eeB4tJh+dfeH9RVlpsSHFhv7tR\nSyOVKZx1lJmRLnTsVmmmyd2U67IcCC3PIAqCAH8wzvPRJFlLDRlpi0kPg159H9NSGo4VMtIqPAJC\nq89pM0oa8bnU2HQYLocJVrP69pnJqMOe7T3wzsZw9KR32fPewog8TmGhyjxuK+wWA/xFrm3KEfdZ\nCxusFqW+T2gqy2kz4ppL12M2lMCxU77C40Njc2iyGxkAkGR2qxF2i0F+Rlqlo69E4odFsXPSsUQa\n8WSGHbtJMpslf+5e5sVLMJJQbbZWPI9abpZ0KJKEzWJQXWd/agynzYRgNImsjHnsqXQG07NRVZ6P\nFl1zaR8A4NevnVn23LQYSDMjTRI5bUZJo3IXGvOG0azSm1GrgZ9ga9CmXheA+YuYSCyFKX8UG7qa\noNFoGrk0UpmOVhsmZ6KyLl5CMfWWpALLM4jZrIC5cAKpdKZwdpp3ZkkqjUYDl9MsKyMtCAKCkaRq\nA+n5jHTpm3ChaLJw9pWoEqfNiGxWQDiWkvw9E74IBAHo8ag3kD6/txkbupz4jz9M4Oe/PYVD/+8k\n/ub7v8XkTISl3SSbI1/ZIQjSrulS6Sy8s1Gewy9D3+gFUP11ti0uyT0zEQQAbOhiZ0eSp63ZglMj\nAYSiSTTZpZ2PUX9pd36WdD4j/d1n3sTv8s05WvMBNCs7SI4WpxnvDc8ikxWg01a+mZlIZpBMZ1Ub\nSHcWRmAVz0jnbhSk0N/NAICkET9/5FRqFM5Ht6o3kNZoNDjwZx/Cf3vsP3Dw8PHC468cm4B3NgaD\nXosmlXX2p8Zx2ozIZAVE42nYJFQNTs5EkBXmb47ScsxIr0FdSy5ihvLno/u7nA1bE6mTOO5Azgzc\nYL6zqlqDgIUZ6cH3pvG7t8fQ7rbi4o0thTEQnbw7SzK4nCZkswKCYWkNx9TeiMtk0KHNZSl5Rjqe\nzCCdyaq2aoVWn/hakNNwTKyI6FZho7GF+jqdeOjOPbhwgxtXbM2NLx0am4M3EENrswVaCTfnXRMD\nMgAAFxRJREFUiID5SsFys8kXEqe28JqnNGak1yCr2QCXw1TISH8wngukmZEmucTM62wwgQ0Sx4/P\nBvMzB1WatRXPP58cnsW/Hx2DVgM8cOsl2NDVhEAogZMjs9h5gafBqyQ1aRGrHObikl4Xap0hvVB3\nqx1vv+9FLJGGxbT4UkNsGuVQ6Y0CWn1N9txekXO+U80zpJfqaLHhoTv3IJsV8PkHf4H3zs4iEEpg\nXbuj0UsjFRFvSAUjycJklnLGfWvnNbRSmJFeo7ra7PDORpFKZ/DB+BwMei26VXxOiBqjOT83cFZG\noyS1zxxscZqh02rw1kkvxrwRXHf5hsJNqGaHCZdc2MHRVyRLaz6Q9gZikr5e7RlpYH7c0NI59IN/\nnMb//qc/AADPSJNk4k2loIxZ0mPeMLRajaSAQS20Wg3WdzZhIt8ElOejSY6FgbQUYlUHz0iXxoz0\nGtXVasPxoRmMeSM4OxlCX4eDF/8km9spv7RbzEirdeag2aTHg1/8MEamQjAadPjE7t5GL4lUTrzY\nFZsDVaL24xHAfAZjzBtGf3fuRlQ6k8VDT/8e0XgabS4LLh3obOQSSUWqK+0Oo91tVeUIuXL6u5tw\n4owfAEdfkTxyS7vFqg6WdpfGQHqNEi9ifvfWKFLpLMu6qSpiGWogJD0LMBuKw2bWw2TQrdSyVtyu\nLe3YtaW90cugNUIMpH0BaTek1kJGWmxOI5YGAsC7H8wgGk/jU5evx1/duJVTJEgyuaXd4WgSc+Ek\nzs9PMVlLxBtTAOBhRppkkJuRHvdF0NpkhtnIcLGUqm/Tvf7667jsssvw4osvFn3+oosuwi233FL4\nL5PJVL1Ikk8swzj80hAA4IptEg+4Ei1QTbOx2VCiUBJORLnu9wDgnZWakVZ/IC2Wdo8vGIH1xolp\nAMClF3UyiCZZxNLuOYml3WKPmC6VNxorZmEgzdJukkPsSxGSEEgnUhn4AjGej66gqlsMw8PDeOKJ\nJ7Bz586SX2O32/H0009XvTCqjbjxE8kM2lwWbN/E5kgkX7PdBI0GhW7VlaQzWQQjSazrYAMUIlGz\nI3fu3ncOnZFud1mh02owOh0qPPbGiUmYjDpcvLGlgSsjNWoSM2kSS7vFjvE9azAI6OtwQKfVIJMV\n0OZiaTdJJ/alkJKRnmTHbkmqyki3tbXhkUcegcPBi2WlWrjxr7qkT9LsUqKldLrcjMpZiRnpufx4\nHzcz0kQFOq0GLU3mKpqNqbPPAJB779i0zoWTwwGcmQhiciaCkakwtp3XBqOKj31QY5hNehgNOsnN\nxsam1263YYNeh3UdDmg0QGszM9IkXaG0W8IZ6dE1MId9NVSVkbZYKr9wk8kkDhw4gLGxMVxzzTW4\n9dZby379yMgIUqlUNctpiKGhoUYvoSKX3YBAJIVN7YIq1ku1W4l/Z5tJA99cTNKfPTKdCxQ0Qpx7\njhY51/eDw6zB0GQM779/Gjpd+RubUzO5kYXeqVH4veq9CbrnIgdOnPHj4M/eRIc7d3Otr02ruL2g\ntPVQcVaTFjOBqKR/r5NnpgAAmZgfQ0OhCl+tXKV+1s98uBX+kBNjI2dXeUWkZulMFgAw7Zur+Dp6\n+93ca8iESNGvPdfeN/v7+4s+XjGQPnToEA4dOrTosbvuugt79uwp+3333nsvbrjhBmg0Guzfvx+7\ndu3CwMBAya/v7VVPZ9yhoaGS/0OV5CufNSMUTeFD2/oavRRaBSu1L9tbpzA2M43O7nXL5sEuNROf\nBHAK63vaVfEaodWhlvfMldTTMYvTE1E0tXTC4y5fjpnKnIHdYsD5521cpdWtjA0bBLzwhzm8fToA\nnA7CbjHgM3sHFDVjnntTPVqahzE6HZb07zUXHYbJqMOOgU2qPY9fbm9yy1K1rOb3kMrqKr6Ogi/5\nAACX7tyElqbFCVS+b86rGEjv27cP+/btk/0H33zzzYVfX3rppTh58mTZQJrq7/KtbDBGtXPlR2DN\nhuKwmMqX+IhnqV0qHX1FtFLmR2DFygbS6UwW/mC80BRGzTQaDf78ms347z99FX0dDtx/6yWKCqJJ\nXZxWIxLJDOLJdNkuwtmsgDFfGN2tdtUG0UQrxWE1Shp/dWY8d/PTzffsslZkuN7Q0BAOHDgAQRCQ\nTqcxODiI888/fyX+KiJaYeKbqDgfupzZUO4stYtnpIkWEc8yVjon/cIbIwhFU9ixqW01lrXidm1p\nxyP3fAzf/S9X8qwd1aTJnrtBW6nhmD8YRyKZWZMdu4lq5bQZEYwkIQhCya+JJ9OYmIlgfZeTN6Mq\nqOqM9JEjR3Dw4EEMDQ3h+PHjePrpp/H444/jsccew+7du7Fjxw50dHTgc5/7HLRaLT7+8Y9j69at\n9V47Ea2CZsd8RrqSQD7YFrPYRJQzP0u6dCCdSmfw7L+9B4Nei5s+uWm1lrbi+jqcjV4CrQELZ+CW\nq+oQO3Z3r8FGY0S1ctiMSKWzSCQzMJc4rjcyFYIgAOv53l1RVYH03r17sXfv3mWP33777YVf33PP\nPVUvioiUQ8xIS5klLZZ2N7O0m2gRKbOkf/P6MLyzMfynj25cdiaN6Fwnfq6cGg3gvN7mkl83LgbS\nHgbSREstHIFVKpA+Mx4EAPR1MpCuZEVKu4lo7RDLtKWWdms16h7bQ7QSxEDaFyh9Q+ro+7nmLp/Z\nwyYuREtduaMHJqMO/+eXJwqjFosZZUaaqCQpI7DOTOYC6fUMpCtiIE1EZS1sNlbJbCiBJruJc8uJ\nlrBZDLCYdJguk5Ee94VhMurgcTEbTbSUx23F/mu3IBRN4vH/e7zk1417IwCArlaekSZayrHgiEQp\nZydygfS6DseqrEnNGEgTUVliafdMmUyaKBCKs9EYUREajQbtbhum/JGiTV4EQcCEL4KuVhubuxCV\n8Jk9/ejx2PHbwVFk8jNxlxrzhtFkN8JuVX/ne6J6EzPSoTKB9JmJINrdVljNhtValmoxkCaissxG\nPZrsxrKZNACYnIkglsiw0RhRCR0tVsQSGcwV6TrsD8YRT2bY2ZqoDJ1Wg43dzchkBfjmlt/cTaWz\nmPJHWdZNVEJLPjnym9eHkUhllj0fT6YxF06ikxUdkjCQJqKKPC4rpmdjyGaLj0sQBAE//tkxAMDe\nD/Wu5tKIVKOjJXdhMjkTWfZcoRyVI3uIyupoyXXsnvIvfx1NzkSQzQoMpIlK2Lm5Hbu2tOPt9734\n5hOvL6uQEsfLsWmsNAykiagij9uKdCZb8pz0q+9M4I0TU9h6Xiuu3NG9yqsjUgfxDv9EsUDal2uQ\nxHOdROW150dfTc4sr5ISO3Z3MZAmKsqg1+L+L+zGxRtbMPjeNIanQoueD+Qb+TXbGUhLwUCaiCpq\nd+UuXKb9xWfg/uLlDwAAX7lxK893EpVQyEj7SmekO1naTVSW+Dqa8i8PpMfyr6NuVnYQlWTQ6/CR\nrV0AgNOjc4ueEzviNzGQloSBNBFV5MlnAEqdk572x9DsMKG3nR0eiUrpbKmckWZJKlF5YkZ6qlhG\nmq8jIkk29uRmsZ8eCyx6fK6QkWazPikYSBNRRe1lAmlBEOCbi6G1mSN7iMrxuCzQaTXFS1J9EVjN\nucZ+RFRaS3P+dVTkjPTodBgaDdgoiaiC9Z1OaDXLM9KB/BlpJzPSkjCQJqKK2vJzbYuV0s2Fk0il\ns2hjIE1Ulk6nhcdlXZaRzmY5+opIKp1WA4/LWvTzaNwbhsdlhUGva8DKiNTDbNKj2+PA0FhgUSPZ\nOZ6RloWBNBFV5CmckV5+4eIN5B5jIE1UWUeLFYFQArFEuvCYLxBDKp3l6CsiidrduddRPDn/OorG\nU5gNJVjWTSTRxp4mxBKZRTd3AzwjLQsDaSKqyGLSw2kzYnp2ebMxXyD3GEu7iSrraF0+AmtkOtc1\nlZ2GiaRpL4zAmr+5O5bv2N3t4euISIrz8uekT43Mn5OeC+UDaRuPGUnBQJqIJPG4rfDORpfNHPQy\nkCaSrLPILOl3P/ADAC7oczVkTURqU2g4tiiQznfs5vloIkk2djcBAE6PzZ+TngsnYTbqYDbpG7Us\nVWEgTUSStLusSKazCOTvVop8gdxsaZZ2E1Umju6Z8M0HAMeHZqDRAFvWuxu1LCJVKYzAWtC4jzOk\nieTpFwPp0fmMdCCcYFm3DAykiUgScQTWz357Gi//YbzwOEu7iaTrXFLanUxlcHJ4Fhu6mmCzGBq5\nNCLVEDPSg+9NIxpPAWBpN5FcVrMB7W4rhidzx4sEQUAwkmCjMRkYSBORJGIA8LMjp/Dtp36Ps5NB\nALlAWqvVwOU0N3J5RKrQkQ8AJny5QPr9kQBS6Swu7m9p5LKIVKWv04kejx1vnJjCXz30AnyBGMa8\nYRj1WrQ28aYukVR9HU4EwgkEQglE4mmkMwIz0jIwkCYiSfbu7MFXbtyKP71qEwDgn148BSB3Rrql\nyQydlmN7iCoxm/RwOUyFLqnHh2YAABcxkCaSzGTQ4X/+zZW47vL18Afj+N1bYxj3htHVZoeWn0VE\nkvV1OgAAw1PBwuirJjsbjUnFQJqIJLGY9Pj0FRvwZ1dvRm+7Hb8dHMWUPwr/XIwZACIZOlps8AZi\nSGeyhUD6wg0MpInkMBv1+NOrLgAAvPjmCGKJDLra2GiMSI51HU4AwNmJUKEHTrODGWmpGEgTkSxa\nrQY37j0PmayAn/z8GLICG40RydHZakM2K2ByJoITZ/zobrPzwoWoCm6nGX0dDpyZyB014gxpInn6\nOnIZ6bOTCzPS/DySioE0Ecl25c5edLfZ8drxSQBAm4uBNJFUYsfh149PIZZIs1s3UQ22b/IUfs1A\nmkieHk/uOMTwZIiBdBUYSBORbAa9Fg/cegks+TmD7NhNJF1nS67h2JHBEQDA5vWcH01Ure2b2gq/\nZiBNJI9Br0N3mw1nJ4Pzpd08Iy0ZA2kiqkpvuwP33rILPR47Bs5rbfRyiFSjI98B/4PxXDnq5j5m\npImqdXF/C/S63OUsZ0gTybeuw4loPI1To3MAmJGWQ9/oBRCReu3a0o5dW9obvQwiVelsmW+IZDXr\n0dvuaOBqiNTNbNLj8q2dGPeG4bQxk0YkV1+HEy8fHcfr707CoNeyylAGBtJERESryGkzwmLSI5ZI\nY9M6F8f1ENXo7j//EDQavo6IqnFhvk9Hd5sNX/6TATisvCElFQNpIiKiVaTRaNDZYsPQ+BzLuonq\ngEE0UfW2bWrDj+79ODpbbYVjEiQN/28RERGtso7WXMMxNhojIqJG6213MIiuAjPSREREq+yTu9ch\nmxVwUX9Lo5dCREREVagqkE6n03jggQcwPDyMTCaDe++9F7t27Vr0NYcPH8ZTTz0FrVaLm266Cfv2\n7avLgomIiNRu94Ud2H1hR6OXQURERFWqKpD+53/+Z1gsFvz93/893n//fXz961/Hc889V3g+Go3i\nhz/8IZ577jkYDAZ87nOfw1VXXYXm5ua6LZyIiIiIiIioEaoqhr/hhhvw9a9/HQDgdrsRCAQWPX/0\n6FEMDAzA4XDAbDZj586dGBwcrH21RERERERERA1WVUbaYDAUfv3UU0/h+uuvX/S8z+eD2z3fidTt\ndsPr9Zb9M0dGRpBKpapZTkMMDQ01eglEy3BfklJxb5JScW+SUnFvklKda3uzv7+/6OMVA+lDhw7h\n0KFDix676667sGfPHjzzzDM4fvw4Hn300bJ/hiAIFRfY29tb8WuUYmhoqOT/UKJG4b4kpeLeJKXi\n3iSl4t4kpeLenFcxkN63b1/RRmGHDh3CCy+8gB/96EeLMtQA4PF44PP5Cr+fnp7G9u3b67BcIiIi\nIiIiosaq6oz0yMgInn32WTzyyCMwmUzLnt+2bRuOHTuGYDCISCSCwcHBZV29iYiIiIiIiNSoqjPS\nhw4dQiAQwO2331547ODBg3jyySexe/du7NixAwcOHMCXvvQlaDQafPWrX4XD4ajboomIiIiIiIga\nRSNIOcBMi/BsACkR9yUpFfcmKRX3JikV9yYpFffmvKpKu4mIiIiIiIjOVQykiYiIiIiIiGRgIE1E\nREREREQkAwNpIiIiIiIiIhkYSBMRERERERHJwK7dRERERERERDIwI01EREREREQkAwNpIiIiIiIi\nIhkYSBMRERERERHJwECaiIiIiIiISAYG0kREREREREQyMJAmIiIiIiIikkHf6AWoyTe/+U0cPXoU\nGo0G999/P7Zu3droJdE56OTJk7jjjjvwhS98Afv378fExATuvfdeZDIZtLW14W//9m9hNBpx+PBh\nPPXUU9Bqtbjpppuwb9++Ri+d1rDvfOc7ePPNN5FOp/GXf/mXGBgY4L6khovFYrjvvvswMzODRCKB\nO+64A5s3b+beJMWIx+O4/vrrcccdd+Cyyy7j3qSGe+211/DXf/3XOP/88wEAmzZtwm233ca9WYxA\nkrz22mvC7bffLgiCIJw6dUq46aabGrwiOhdFIhFh//79woMPPig8/fTTgiAIwn333Sf88pe/FARB\nEL773e8KzzzzjBCJRISrr75aCAaDQiwWEz796U8Ls7OzjVw6rWGvvPKKcNtttwmCIAh+v1+48sor\nuS9JEX7xi18Ijz32mCAIgjA6OipcffXV3JukKN/73veEG2+8UXj++ee5N0kRXn31VeGuu+5a9Bj3\nZnEs7ZbolVdewSc/+UkAwMaNGzE3N4dwONzgVdG5xmg04ic/+Qk8Hk/hsddeew2f+MQnAAAf+9jH\n8Morr+Do0aMYGBiAw+GA2WzGzp07MTg42Khl0xq3e/du/N3f/R0AwOl0IhaLcV+SIlx33XX48pe/\nDACYmJhAe3s79yYpxunTp3Hq1Cns3bsXAD/PSbm4N4tjIC2Rz+eDy+Uq/N7tdsPr9TZwRXQu0uv1\nMJvNix6LxWIwGo0AgJaWFni9Xvh8Prjd7sLXcL/SStLpdLBarQCA5557Dh/96Ee5L0lRPv/5z+Pu\nu+/G/fffz71JivHQQw/hvvvuK/yee5OU4tSpU/jKV76Cm2++GS+//DL3Zgk8I10lQRAavQSiZUrt\nS+5XWg2/+c1v8Nxzz+Hxxx/H1VdfXXic+5Ia7dlnn8WJEydwzz33LNp33JvUKD//+c+xfft29Pb2\nFn2ee5MaZf369bjzzjvxqU99CiMjI/iLv/gLZDKZwvPcm/MYSEvk8Xjg8/kKv5+enkZbW1sDV0SU\nY7VaEY/HYTabMTU1BY/HU3S/bt++vYGrpLXupZdewqOPPoqf/vSncDgc3JekCO+88w5aWlrQ2dmJ\nLVu2IJPJwGazcW9Swx05cgQjIyM4cuQIJicnYTQa+b5JitDe3o7rrrsOALBu3Tq0trbi2LFj3JtF\nsLRboiuuuAK//vWvAQDHjx+Hx+OB3W5v8KqIgMsvv7ywN//1X/8Ve/bswbZt23Ds2DEEg0FEIhEM\nDg5i165dDV4prVWhUAjf+c538OMf/xjNzc0AuC9JGd544w08/vjjAHJHtKLRKPcmKcL3v/99PP/8\n8/jHf/xH7Nu3D3fccQf3JinC4cOHcfDgQQCA1+vFzMwMbrzxRu7NIjTCuZiHr9LDDz+MN954AxqN\nBt/4xjewefPmRi+JzjHvvPMOHnroIYyNjUGv16O9vR0PP/ww7rvvPiQSCXR1deFb3/oWDAYDfvWr\nX+HgwYPQaDTYv38/brjhhkYvn9aof/iHf8APfvADbNiwofDYt7/9bTz44IPcl9RQ8XgcDzzwACYm\nJhCPx3HnnXfi4osvxte+9jXuTVKMH/zgB+ju7sZHPvIR7k1quHA4jLvvvhvBYBCpVAp33nkntmzZ\nwr1ZBANpIiIiIiIiIhlY2k1EREREREQkAwNpIiIiIiIiIhkYSBMRERERERHJwECaiIiIiIiISAYG\n0kREREREREQyMJAmIiIiIiIikoGBNBEREREREZEMDKSJiIiIiIiIZPj/onaUJS5z6zEAAAAASUVO\nRK5CYII=\n",
            "text/plain": [
              "<Figure size 1209.6x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "YyjwHUwZfg9B",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "## Hyperparameters"
      ]
    },
    {
      "metadata": {
        "id": "-gp8Qw-6fg9C",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "RNN_CELLSIZE = 80 # size of the RNN cells\n",
        "SEQLEN = 32       # unrolled sequence length\n",
        "BATCHSIZE = 30    # mini-batch size\n",
        "DROPOUT = 0.3     # dropout regularization: probability of neurons being dropped. Should be between 0 and 0.5"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "WbsuSalyfg9E",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "## Visualize training sequences\n",
        "This is what the neural network will see during training."
      ]
    },
    {
      "metadata": {
        "id": "kYk8zx6jfg9F",
        "colab_type": "code",
        "outputId": "f475a2b0-9d84-469a-c8c8-c4337d949e71",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 426
        }
      },
      "cell_type": "code",
      "source": [
        "# The function dumb_minibatch_sequencer splits the data into batches of sequences sequentially.\n",
        "for features, labels in dumb_minibatch_sequencer(data, BATCHSIZE, SEQLEN, nb_epochs=1):\n",
        "    break\n",
        "print(\"Features shape: \" + str(features.shape))\n",
        "print(\"Labels shape: \" + str(labels.shape))\n",
        "print(\"Excerpt from first batch:\")\n",
        "\n",
        "picture_this_7(features)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Features shape: (30, 32)\n",
            "Labels shape: (30, 32)\n",
            "Excerpt from first batch:\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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TJkzg5ptvZv78+cyfP5/y8nKFUgohOlJDUxvL1mRgo9dy7/UxVvfd323XKB+v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hbMvLcPFUaF/3wWTZnUW5NVUFTGSx/tZdch2RSzORQWlxMVl4aPpz2+zfBGXLQctw3xw9nekm93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\nEEIIIYS4hHSUhRBCCCGEEEKIS/w/ahT4/U5vx3sAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 1209.6x432 with 6 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "8PB4I6Qafg9H",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "## The model\n",
        "\n",
        "![deep RNN schematic](https://googlecloudplatform.github.io/tensorflow-without-a-phd/images/RNN1.svg)\n",
        "<div style=\"text-align: right; font-family: monospace\">\n",
        "  X shape [BATCHSIZE, SEQLEN, 1]<br/>\n",
        "  Y shape [BATCHSIZE, SEQLEN, 1]<br/>\n",
        "  H shape [BATCHSIZE, RNN_CELLSIZE*NLAYERS]\n",
        "</div>\n",
        "In Keras layers, the batch dimension is implicit ! For a shape of [BATCHSIZE, SEQLEN, 1], you write [SEQLEN, 1]. In pure Tensorflow however, this is NOT the case."
      ]
    },
    {
      "metadata": {
        "id": "9ga_jncykosN",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "def keras_model(batchsize, seqlen):\n",
        "  l = tf.keras.layers  # syntax shortcut\n",
        "\n",
        "  model = tf.keras.Sequential([\n",
        "    l.Reshape([seqlen, 1], input_shape=[seqlen,], batch_size=batchsize), # [BATCHSIZE, SEQLEN, 1] is necessary for RNN model\n",
        "    l.GRU(RNN_CELLSIZE, stateful=True, return_sequences=True), # output shape [BATCHSIZE, SEQLEN, RNN_CELLSIZE]\n",
        "    l.GRU(RNN_CELLSIZE, stateful=True, return_sequences=True), # output shape [BATCHSIZE, SEQLEN, RNN_CELLSIZE]\n",
        "    l.TimeDistributed(l.Dense(1)), # output shape [BATCHSIZE, SEQLEN, 1]\n",
        "    l.Reshape([seqlen,])           # output shape [BATCHSIZE, SEQLEN]\n",
        "  ])\n",
        "  \n",
        "  # keras does not have a pre-defined metric for Root Mean Square Error. Let's define one.\n",
        "  def rmse(y_true, y_pred): # Root Mean Squared Error\n",
        "    return tf.sqrt(tf.reduce_mean(tf.square(y_pred - y_true)))\n",
        "\n",
        "  # to finalize the model, specify the loss, the optimizer and metrics\n",
        "  model.compile(\n",
        "     loss = 'mean_squared_error',\n",
        "     optimizer = 'adam',\n",
        "     metrics = [rmse])\n",
        "  \n",
        "  return model"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "8311WBkinlGp",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# Keras model callbacks\n",
        "\n",
        "# This callback records a per-step loss history instead of the average loss per\n",
        "# epoch that Keras normally reports. It allows you to see more problems.\n",
        "class LossHistory(tf.keras.callbacks.Callback):\n",
        "  def on_train_begin(self, logs={}):\n",
        "      self.history = {'loss': []}\n",
        "  def on_batch_end(self, batch, logs={}):\n",
        "      self.history['loss'].append(logs.get('loss'))\n",
        "      \n",
        "# This callback resets the RNN state at each epoch\n",
        "class ResetStateCallback(tf.keras.callbacks.Callback):\n",
        "  def on_epoch_begin(self, batch, logs={}):\n",
        "      self.model.reset_states()\n",
        "      print('reset state')\n",
        "\n",
        "reset_state = ResetStateCallback()\n",
        "      \n",
        "# learning rate decay callback\n",
        "#def lr_schedule(epoch): return 0.01\n",
        "def lr_schedule(epoch): return 0.0001 + 0.01 * math.pow(0.8, epoch)\n",
        "lr_decay = tf.keras.callbacks.LearningRateScheduler(lr_schedule, verbose=True)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "XlKtnYjbfg9V",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "## The training loop"
      ]
    },
    {
      "metadata": {
        "id": "Tcrj-e50yyuM",
        "colab_type": "code",
        "outputId": "e9b7e607-3967-4263-835c-3d7e7cb33f94",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 614
        }
      },
      "cell_type": "code",
      "source": [
        "# Execute this cell to reset the model\n",
        "\n",
        "NB_EPOCHS = 8\n",
        "model = keras_model(BATCHSIZE, SEQLEN)\n",
        "\n",
        "# this prints a description of the model\n",
        "model.summary()\n",
        "\n",
        "display_lr(lr_schedule, NB_EPOCHS)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "reshape_20 (Reshape)         (30, 32, 1)               0         \n",
            "_________________________________________________________________\n",
            "gru_20 (GRU)                 (30, 32, 80)              19680     \n",
            "_________________________________________________________________\n",
            "gru_21 (GRU)                 (30, 32, 80)              38640     \n",
            "_________________________________________________________________\n",
            "time_distributed_10 (TimeDis (30, 32, 1)               81        \n",
            "_________________________________________________________________\n",
            "reshape_21 (Reshape)         (30, 32)                  0         \n",
            "=================================================================\n",
            "Total params: 58,401\n",
            "Trainable params: 58,401\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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bKXg3qs6Et5pgaFAyi5LiykFpI3lQPgdBQUH4+/tTt25dxWJQOgclgeTgCcmD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\n",
            "text/plain": [
              "<Figure size 648x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "UM0AIbCSfg9V",
        "colab_type": "code",
        "cellView": "both",
        "outputId": "1c4272bd-37c5-46db-f67a-e106cffd0ddf",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 570
        }
      },
      "cell_type": "code",
      "source": [
        "# You can re-execute this cell to continue training\n",
        "\n",
        "steps_per_epoch = (DATA_LEN-1) // SEQLEN // BATCHSIZE\n",
        "generator = rnn_minibatch_sequencer(data, BATCHSIZE, SEQLEN, NB_EPOCHS)\n",
        "#generator = dumb_minibatch_sequencer(data, BATCHSIZE, SEQLEN, NB_EPOCHS)\n",
        "full_history = LossHistory()\n",
        "history = model.fit_generator(generator,\n",
        "                              steps_per_epoch=steps_per_epoch,\n",
        "                              epochs=NB_EPOCHS,\n",
        "                              shuffle=False,\n",
        "                              callbacks=[lr_decay, full_history]) # Can add reset_state"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\n",
            "Epoch 00001: LearningRateScheduler reducing learning rate to 0.0101.\n",
            "Epoch 1/8\n",
            "136/136 [==============================] - 11s 81ms/step - loss: 0.0272 - rmse: 0.1222\n",
            "\n",
            "Epoch 00002: LearningRateScheduler reducing learning rate to 0.0081.\n",
            "Epoch 2/8\n",
            "136/136 [==============================] - 8s 59ms/step - loss: 0.0070 - rmse: 0.0834\n",
            "\n",
            "Epoch 00003: LearningRateScheduler reducing learning rate to 0.0065000000000000014.\n",
            "Epoch 3/8\n",
            "136/136 [==============================] - 8s 59ms/step - loss: 0.0064 - rmse: 0.0799\n",
            "\n",
            "Epoch 00004: LearningRateScheduler reducing learning rate to 0.0052200000000000015.\n",
            "Epoch 4/8\n",
            "136/136 [==============================] - 8s 59ms/step - loss: 0.0053 - rmse: 0.0731\n",
            "\n",
            "Epoch 00005: LearningRateScheduler reducing learning rate to 0.004196000000000001.\n",
            "Epoch 5/8\n",
            "136/136 [==============================] - 8s 61ms/step - loss: 0.0049 - rmse: 0.0701\n",
            "\n",
            "Epoch 00006: LearningRateScheduler reducing learning rate to 0.0033768000000000005.\n",
            "Epoch 6/8\n",
            "136/136 [==============================] - 8s 60ms/step - loss: 0.0046 - rmse: 0.0679\n",
            "\n",
            "Epoch 00007: LearningRateScheduler reducing learning rate to 0.0027214400000000008.\n",
            "Epoch 7/8\n",
            "136/136 [==============================] - 8s 60ms/step - loss: 0.0044 - rmse: 0.0664\n",
            "\n",
            "Epoch 00008: LearningRateScheduler reducing learning rate to 0.002197152000000001.\n",
            "Epoch 8/8\n",
            "136/136 [==============================] - 8s 59ms/step - loss: 0.0043 - rmse: 0.0654\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "u_TxVHXPfg9Y",
        "colab_type": "code",
        "outputId": "aeb0a870-ab66-4046-b22a-a09b11f2d89d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 388
        }
      },
      "cell_type": "code",
      "source": [
        "display_loss(history.history, full_history.history, NB_EPOCHS)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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NRgwGxznrStilQXi2wq9cGbg4REREREQkaChZrwPPNnhHsm4A7FhtStalAdx6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\ngg==\n",
            "text/plain": [
              "<Figure size 1209.6x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "xBmt2uUVfg9N",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "## Inference\n",
        "This is a generative model: run one trained RNN cell in a loop"
      ]
    },
    {
      "metadata": {
        "id": "UFalPiNOr2pt",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# Inference from stateful model\n",
        "def keras_prediction_run(model, prime_data, run_length):\n",
        "  model.reset_states()\n",
        "  \n",
        "  data_len = prime_data.shape[0]\n",
        "  \n",
        "  #prime_data = np.expand_dims(prime_data, axis=0) # single batch with everything\n",
        "  prime_data = np.expand_dims(prime_data, axis=-1) # each sequence is of size 1\n",
        "  \n",
        "  # prime the state from data\n",
        "  for i in range(data_len - 1): # keep last sample to serve as the input sequence for predictions\n",
        "    model.predict(np.expand_dims(prime_data[i], axis=0))\n",
        "  \n",
        "  # prediction run\n",
        "  results = []\n",
        "  Yout = prime_data[-1] # start predicting from the last element of the prime_data sequence\n",
        "  for i in range(run_length+1):\n",
        "    Yout = model.predict(Yout)\n",
        "    results.append(Yout[0,0]) # Yout shape is [1,1] i.e one sequence of one element\n",
        "\n",
        "  return np.array(results)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "DBVi1tNofg9a",
        "colab_type": "code",
        "outputId": "fcd66eee-feee-4168-e773-5f47445f8749",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 405
        }
      },
      "cell_type": "code",
      "source": [
        "PRIMELEN=256\n",
        "RUNLEN=512\n",
        "OFFSET=20\n",
        "RMSELEN=128\n",
        "\n",
        "prime_data = data[OFFSET:OFFSET+PRIMELEN]\n",
        "\n",
        "# For inference, we need a single RNN cell (no unrolling)\n",
        "# Create a new model that takes a single sequence of a single value (i.e. just one RNN cell)\n",
        "inference_model = keras_model(1, 1)\n",
        "# Copy the trained weights into it\n",
        "inference_model.set_weights(model.get_weights())\n",
        "\n",
        "results = keras_prediction_run(inference_model, prime_data, RUNLEN)\n",
        "\n",
        "picture_this_8(data, prime_data, results, OFFSET, PRIMELEN, RUNLEN, RMSELEN)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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fcYD3b135XrSzzYXBIHFFx2zftDdIPCGnMsXroSoXRKOljUEoHKN72MvWpvJV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\n+coPh/jC772HqnVG2Wx2fK8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Xg7vMmhrZthbvOqgoF157q7iUCxOzoaw6XqtoKfH3eEM5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GmaS0G16qel7Z+Z4oJRBVG5v6rHmPTfg8Tv79227l3z0sky9Ve5Zb+3ezqaPxBMhNQ5JJ+eKZ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\nAADg8xuSD7aiDVpbfAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 1209.6x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "RMSE on 128 predictions (shaded area): 0.05800183856270835\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "AQn6WA-pfg9c",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Copyright 2018 Google LLC\n",
        "\n",
        "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
        "you may not use this file except in compliance with the License.\n",
        "You may obtain a copy of the License at\n",
        "[http://www.apache.org/licenses/LICENSE-2.0](http://www.apache.org/licenses/LICENSE-2.0)\n",
        "Unless required by applicable law or agreed to in writing, software\n",
        "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
        "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
        "See the License for the specific language governing permissions and\n",
        "limitations under the License."
      ]
    }
  ]
}